Quality and safety in health and social care services remains a contentious and difficult problem to solve. Quality care means different things in different contexts. For example, in a hospital setting, one measure of quality may be in-hospital mortality.1 Conversely, in a nursing home setting, where the expectation is that a person will live out his or her last days, quality may be measured in terms of injuries related to falls2 or the proportion of residents admitted to hospital.3

Measuring quality is only one piece of a larger puzzle. Researchers are constantly searching for factors that are associated with quality to inform practice and policy development that could potentially benefit service users, that is, quality improvement. The field of quality improvement research is often delineated by a conceptualization of quality as contingent on structures (e.g., buildings and staff) and/or processes (e.g., care activities or governance arrangements).4 Thus, research may focus on whether there is an association of a quality outcome and organizational, environmental, and staffing characteristics, such as nurse staffing levels5 or geographic location.6 Similarly, the focus may fall on whether there is an association of a quality outcome and process factors, such as operating theater cleaning practices7 or the use of a vacuum system for wound dressings.8

A common intervention to drive quality improvement in health and social care is regulation. Regulation can be defined as “sustained and focused control exercised by a public agency over activities which are valued by a community.”9 In health and social care services, regulation usually entails periodic inspections or site visits that judge compliance with written standards, mandatory reporting of prescribed events, and a variety of enforcement powers that can be leveraged in the event that a service is not in compliance.10 In terms of mandatory reporting, adverse events (AEs) are typical of the types of information that service providers must notify to a regulator. Reporting requirements differ between countries and care settings but often includes inter alia unexpected death, serious injury, excessive radiation exposure, staff misconduct, medication error, or abuse allegations.11–15

Adverse events can serve as useful indicators of quality. Adverse events can be defined as an unintended or unexpected incident that causes harm and may lead to temporary or permanent disability.16 Adverse events can also be defined as unintended injuries or complications caused by the management of a patient’s health care rather than by the patient’s underlying disease.17 These definitions generally apply to acute settings. In residential care facilities (RCFs), the interpretation of AEs is typically broader and applies to events that have a potential or actual impact on the quality and safety of care and the well-being of residents. The term SI has been used in the literature as a more generic term that encompasses AEs and other events.18 As such, we use the term SI in this article.

Some researchers have used the severity of SI (in terms of harm to service users) in addition to, or in place of, incidence of SI as the outcome measure.19,20 There is merit in this approach as it accounts for the degree to which service users were impacted by SI in comparison to other measures such as frequency or incidence. Measures of severity may include a clinician grading system21 or a risk rating system applied by a regulator.11

Although SIs in hospitals have been the subject of intensive research—often attributed to the seminal report on patient safety To Err Is Human22—the topic of SI in social care has received much less attention. The literature on SI in social care settings and their contributory factors is limited, and sample sizes of studies have typically been small. From the limited research, there is evidence that SIs occur in social care services. Health care–associated infections (20.0%), falls (18.5%), and pressure ulcers (17.4%) were the most common types of SI reported in a review of 600 patient records of people receiving homecare in Sweden.23 A total of 2000 SIs were estimated to have occurred in Italian nursing homes during the 3-month period representing the onset of the COVID-19 pandemic, which equated to an estimated incidence rate of 2.1 per 100 nursing home residents in the 3-month period or 8.4 per 100 residents per year.24 A study of social care services (nursing homes and residential disability services) in Ireland reported on SI data such as unexpected deaths, serious injuries, and outbreaks of infectious disease during a 6-year period.11 Among the findings, the authors reported an incidence rate for serious injuries of 11.3 per 100 beds in nursing homes and 19.2 per 100 beds for disability services for 2019.11 In a study of nursing homes in Sweden, medication errors, falls, delayed/inappropriate intervention, and missed nursing care accounted for 89% of SIs.19 Although the other studies did not investigate contributing factors, the authors of this study identified the most frequent factors as lack of competence, incorrect/lack of documentation, and teamwork failure.

There is a substantial literature on associations of organizational, environmental, and staffing characteristics and quality in social care services. For example, research has been carried out on the size of services,25–27 staff levels,28,29 for-profit status,30 and urban/rural location.31,32 The evidence suggests that smaller services with higher staffing levels tend to provide better quality. Services that are not-for-profit and located in an urban setting also show associations with higher quality.30–32 However, most of the aforementioned findings are applicable only to nursing homes, and these studies used a variety of quality measures. We have found very few studies that include residential disability services in their analysis and none that use the risk associated with SI as the quality outcome measure.

Given the identified gap in the literature in terms of the association of organizational, environmental, and staffing characteristics and SI in RCF, the aim of this study was to use a national database of SI reported by nursing homes and residential disability services in Ireland to investigate the association of these characteristics and the severity of SI notifications.

METHODS Data

The Irish 2007 Health Act33 stipulates the requirement of RCFs to submit statutory notifications of SI to the regulator in Ireland. Notifications are required to be submitted to the regulator for SI such as unexpected death, use of restrictive practice, serious injury, pressure sores, or allegations of abuse, among others.

The Database of Statutory Notifications from Social Care in Ireland was used for these analyses (hereafter “the database”). The database contains all statutory notifications received by the regulator of RCF for older persons (RCF-Nursing home) and for people with disability (RCF-Disability) from 2013 to 2022.34

Setting

In Ireland, RCF-Nursing home and RCF-Disability are regulated by the national regulator for health and social care services. RCF-Nursing home is defined in law as “an institution for the care and maintenance of more than two dependent persons,” with certain exclusions applying such as services providing psychiatric or acute care.35 In practice, RCF-Nursing home in Ireland provides services to older people in need of residential care. There were 557 RCF-Nursing homes in Ireland at the end of 2022, providing a total of 31,674 beds, with a mean beds per home nationally of 56.9.36 More than 3 quarters of RCF-Nursing homes in Ireland are owned and operated by private, for-profit providers, with the remainder being composed of government-owned (20%) and voluntary (not-for-profit) providers (3%).36

RCF-Disability in Ireland is defined as “an institution…at which residential services are provided…to persons with disabilities, in relation to their disabilities.”33 In practice, such services mostly provide residential care to adults and children with intellectual disabilities, with a smaller number caring for those with physical and/or sensory disabilities.36 There were 1478 RCF-Disability services at the end of 2022 in Ireland, providing 9030 beds, with a mean beds per center nationally of 6.1. Provider organizations of RCF-Disability are mostly voluntary (not-for-profit); around 12% are provided directly by government (statutory).36

Ethical Approval

Ethical approval was not sought for this analysis as it was secondary data from notifications and does not include personal identifiable data or data collected at the level of the person. These data pertain to events and not people. Ethical approval was sought for the patient and public engagement that was undertaken as part of the wider research project on statutory notifications and development of the Database of Statutory Notifications from Social Care in Ireland, as it involved a vulnerable population group. Ethical approval to engage with people with disability and older people living in RCF, for patient/public involvement purposes, was granted by the Research Ethics Subcommittee of the Daughters of Charity Disability Support Service Ethics Committee on January 26, 2021, and the St. James’ Hospital/Tallaght University Hospital joint research ethics committee on June 29, 2021.

Patient and Public Involvement

Telephone and video call interviews were conducted with residents in RCF-Disability (n = 6) and RCF-Nursing home (n = 3) during the development of the Database of Statutory Notifications from Social Care in Ireland.37 Opinions from residents were sought on publishing the data open access and using it for research purposes. Residents were also asked about the type of questions they would like researchers to ask of the data, who dissemination of the findings should target, and dissemination formats that they considered appropriate for residents. Contributions from the residents were used to inform the prioritization of analyses using the database, including this analysis, and to inform dissemination strategies and formats.

Sample

Our sample included all statutory notifications of SI to the regulator from RCF-Disability and RCF-Nursing home in Ireland during the years 2018 to 2019 inclusive (n = 53,945). Nil returns (i.e., notifications submitted by an RCF to state no SI had occurred) were removed (n = 677). A total of 53,268 notifications remained for analysis.

Outcome: Risk Rating of Notifications

Risk rating is carried out by an inspector who is responsible for monitoring the RCF that submitted the notification. The risk rating is a combination of 2 values: the risk likelihood and the risk impact, both of which are included in the database for each notification. These values range from 1, the lowest risk, to 5, the highest risk. The regulator’s system then multiplies these values to derive the risk rating for the notification, with the lowest possible value being 1 and the highest being 25.

The mean risk rating of all SI notifications received from each RCF in the sample was calculated and used as the outcome.

Exposure: RCF Characteristic

Organizational, environmental, and staffing characteristics available in the database were used to examine the association of characteristics and mean risk rating of SI notifications from RCF. These were beds (mean of registered beds for 2018 and 2019), service type (RCF-Nursing home or RCF-Disability), total staff full-time equivalent (FTE), nursing staff FTE, provider size (number of RCF operated by the service provider), provider type (non-statutory [for-profit or not-for-profit] or statutory, i.e., government-provided). Total staff to bed ratio and nursing staff to bed ratio were calculated as staff number/number of registered beds and nursing staff number/number of registered beds at RCF level, and also used as exposures.

Where characteristics of an RCF differed over the 2 years, the mean of the characteristic was used for continuous variables and the most recent for categorical variables.

Covariates

We calculated the notifications per registered bed for each RCF during the 2-year period for inclusion as a covariate. This was to account for RCFs that may only have been operational for a short time during the 2-year period, thereby limiting their opportunity to submit notifications for SI and for larger RCFs submitting more notifications and therein increasing the opportunity to submit more severe notifications.

Statistical Analyses

Characteristics of RCFs were described as n (%), mean ± SD, or median (interquartile range [IQR]), as appropriate.

The sample was complete for services active in Ireland in the study years and notifications received by the regulator. Covariates included in the regression analysis were imputed to account for missingness, with missing data points for continuous variables replaced with the respective median. Included categorical variables were void of missingness.

Linear regression of the association of RCF characteristics and mean risk rating of SI notifications was conducted using the following models: model 1, unadjusted; model 2, adjusted for number of notifications per bed; and model 3, additionally mutually adjusted for the other RCF characteristics examined.

All RCF characteristics were examined for interaction with each other by inclusion of each as an interaction term in model 3. There was an interaction of service type and all other RCF characteristics for all exposures (P > 0.001). As such, analyses were stratified by service type and conducted separately for each. Upon stratification, we observed an interaction of total staff FTE and mean beds. We thus created model 4 adding total staff FTE and mean beds as an interaction term to model 3, for all exposures. After which, no other interactions were significant (P > 0.115).

In sensitivity analyses, analyses were repeated in complete cases only, using model 4, to examine the effect of the imputation.

Statistical analyses were performed in R Studio (version 2022.02.3).38 A P value <0.05 was considered significant.

The reporting of this study was done in line with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional checklist (Supplemental Fig. 1, https://links.lww.com/JPS/A594).39

RESULTS

There were 594 RCF-Nursing homes and 1304 RCF-Disability services operational during the 2-year period (Table 1). Registered beds in RCF-Nursing home had medians (IQRs) of 48.5 (33.0–64.0) and 6.0 (4.0–9.0) for RCF-Disability. Mean ± SD risk rating of all SI notifications nationally for RCF-Nursing home was 4.56 ± 1.01, and that for RCF-Disability was 3.85 ± 1.22. Mean risk rating per notification type ranged from 2.68 ± 1.47 to 6.00 ± 1.89 (Supplementary File 1, https://links.lww.com/JPS/A582).

TABLE 1 - Descriptive Statistics for RCFs Operating at Any Point in 2018 and 2019, by Service Type, in Ireland RCF-Nursing Home RCF-Disability n Summary Statistic n Summary Statistic Service type (% of total) 594 31.3% 1306 68.7% Registered beds*, median (IQR) 594 48.5 (33.0–64.0) 1306 6.0 (4.0–9.0) Notifications (% of total) 20,887 39.2 32,381 60.8 Notifications per bed in 2018, median (IQR) 582 0.3 (0.2–0.4) 1164 1.4 (0.9–2.3) Notifications per bed in 2019, median (IQR) 583 0.4 (0.3–0.5) 1245 1.7 (1.1–3.0) Notifications per bed, median (IQR) 594 0.6 (0.5–0.8) 1306 3.0 (1.8–5.1) Total notification mean risk rating, mean ± SD 594 4.6 ± 1.0 1306 3.8 ± 1.2 Total staff FTE, median (IQR) 594 43.7 (30.4–63.2) 1306 10.2 (6.3–15.3) Nursing staff FTE, median (IQR) 594 9.0 (6.0–13.0) 1306 0.0 (0.0–2.0) Total staff to bed ratio, median (IQR) 594 0.9 (0.8–1.1) 1306 1.7 (1.2–2.5) Nursing staff to bed ratio, median (IQR) 594 0.2 (0.1–0.3) 1306 0.0 (0.0–0.3) Provider size, median (IQR) 404 1.0 (1.0–1.0) 84 4.5 (2.0–14.0) Provider type  Nonstatutory RCF (% of total) 469 79.0% 1165 89.2%  Statutory RCF (% of total) 125 21.0% 141 10.8%

*The mean of registered beds for 2018 and 2019.

RCF-Nursing Home

In unadjusted linear regression (model 1), beds (β coefficient [95% confidence interval] = 0.006 [0.003–0.009]), staff FTE (0.003 [0.001–0.005]), nursing staff FTE (0.017 [0.009–0.026]), and mean risk rating for SI notifications were positively associated in RCF-Nursing home (Table 2). The associations of staff to bed ratio, nursing staff to bed ratio, provider size and provider type, and mean risk rating of SI notifications were not significant.

TABLE 2 - Linear Regression of the Association of Structural Characteristics and Mean Risk Rating of Serious Incident, by Service Type (RCF-Nursing Home, n = 594; RCF-Disability, n = 1306) RCF-Nursing Home Model 1 Model 2 Model 3 Model 4 β Coefficient CI β Coefficient CI β Coefficient CI β Coefficient CI Beds 0.006 (0.003 to 0.009) 0.007 (0.004 to 0.009) 0.002 (−0.004 to 0.008) 0.006 (−0.001 to 0.013) Staff to bed ratio −0.093 (−0.249 to 0.062) −0.097 (−0.252 to 0.058) −0.081 (−0.584 to 0.423) −0.205 (−0.723 to 0.314) Nurse to bed ratio −0.036 (−0.690 to 0.618) −0.088 (−0.741 to 0.566) −0.956 (−2.733 to 0.820) −0.629 (−2.434 to 1.176) Staff FTE 0.003 (0.001 to 0.005) 0.003 (0.001 to 0.005) 0.000 (−0.010 to 0.009) 0.005 (−0.006 to 0.016) Nursing staff FTE 0.017 (0.009 to 0.026) 0.019 (0.010 to 0.028) 0.023 (−0.010 to 0.055) 0.019 (−0.013 to 0.052) Provider size 0.000 (0.000 to 0.001) 0.000 (−0.001 to 0.001) 0.003 (−0.002 to 0.009) 0.508 (0.223 to 0.793) Provider type  Nonstatutory Ref Ref Ref Ref Ref Ref Ref Ref  Statutory 0.074 (−0.126 to 0.274) 0.054 (−0.146 to 0.254) −0.800 (−2.185 to 0.586) −0.569 (−1.972 to 0.834) RCF-Disability Model 1 Model 2 Model 3 Model 4 β Coefficient CI β Coefficient CI β Coefficient CI β Coefficient CI Beds 0.044 (0.033 to 0.055) 0.058 (0.047 to 0.069) 0.057 (0.039 to 0.074) 0.081 (0.060 to 0.101) Staff to bed ratio 0.118 (0.078 to 0.158) 0.073 (0.030 to 0.116) 0.077 (0.026 to 0.129) 0.068 (0.017 to 0.120) Nurse to bed ratio 0.461 (0.271 to 0.651) 0.519 (0.332 to 0.706) 0.559 (0.258 to 0.860) 0.356 (0.044 to 0.667) Staff FTE 0.029 (0.023 to 0.035) 0.029 (0.024 to 0.035) 0.010 (−0.001 to 0.020) 0.029 (0.015 to 0.042) Nursing staff FTE 0.054 (0.036 to 0.072) 0.064 (0.047 to 0.082) −0.042 (−0.077 to −0.006) −0.016 (−0.053 to 0.021) Provider size 0.000 (−0.001 to 0.000) 0.000 (−0.001 to 0.001) 0.066 (0.049 to 0.083) 0.067 (0.050 to 0.084) Provider type  Nonstatutory Ref Ref Ref Ref Ref Ref Ref Ref  Statutory 0.123 (−0.091 to 0.336) 0.169 (−0.041 to 0.379) 0.168 (−0.158 to 0.495) 0.120 (−0.002 to −0.001)

Model 1: unadjusted; model 2: adjusted for notifications per bed; model 3, additionally mutually adjusted for structural characteristics; model 4, additional adjustment for interaction term for staff FTE and beds.

After adjustment for notifications per bed (model 2), the positive associations of beds (0.007 [0.004–0.009]), staff FTE (0.003 [0.001–0.005]), nursing staff FTE (0.019 [0.010–0.028]), and mean risk rating of SI notifications remained. The association of provider size and mean risk rating became not significant.

After additional mutual adjustment for RCF characteristics (model 3), none of the exposure variables were significantly associated with mean risk rating for SI notifications.

The association of provider size (0.508 [0.223–0.793]) and mean risk rating became significant after the addition of an interaction term for staff FTE and beds (model 4).

RCF-Disability

In the unadjusted model (model 1), beds (0.044 [0.033–0.055]), staff to bed ratio (0.118 [0.078–0.158]), nurse to bed ratio (0.461 [0.271–0.651]), staff FTE (0.029 [0.023–0.035]), nursing staff FTE (0.054 [0.036–0.072]), and mean risk rating were positively associated in RCF-Disability (Table 2). All other variables examined (provider size, provider type) were not significantly associated.

After adjustment for notifications per bed (model 2), the significant associations remained: beds (0.058 [0.047–0.069]), staff to bed ratio (0.073 [0.030–0.116]), nurse to bed ratio (0.519 [0.332–0.706]), staff FTE (0.029 [0.024–0.035]), and nursing staff FTE (0.064 [0.047–0.082]).

After additional mutual adjustment for RCF characteristics (model 3), the association of staff FTE and mean risk rating was attenuated and became not significant (0.010 [−0.001 to 0.020]). The association of nursing staff FTE became significantly inversely associated (−0.042 [−0.077 to −0.006]). The association of beds (0.057 [0.039–0.074]), staff to bed ratio (0.077 [0.026–0.129]), and nurse to bed ratio (0.559 [0.258–0.860]) remained.

After the addition of an interaction term for staff FTE and mean beds (model 4), the association of nursing staff FTE and mean risk was attenuated and became not significant (−0.016 [−0.053 to 0.021]). The association of staff FTE and mean risk became significant (0.029 [0.015–0.042]). The association of beds (0.081 [0.060–0.101]), staff to bed ratio (0.068 [0.017–0.120]), and nurse to bed ratio (0.356 [0.044–0.667]) remained.

Sensitivity Analysis

When analyses were repeated in complete cases only, using model 4, only marginal differences were noted with no change to the overall interpretation of the findings, suggesting the suitability of the imputation (Supplementary File 2, https://links.lww.com/JPS/A583).

DISCUSSION

The aim of this study was to investigate the association of various organizational, environmental, and staffing characteristics and severity of SI notifications. The analysis was stratified by service type (i.e., RCF-Nursing home and RCF-Disability), and we observed different findings across both settings.

RCF-Nursing Home

One characteristic for RCF-Nursing home, provider size, and mean risk rating of SI notifications was associated in the most adjusted model. The size of a provider (i.e., the number of nursing homes owned or operated by the same company or organization) has been a factor of interest in research on nursing home quality. Nursing home chains exist to varying degrees internationally, with the 5 largest chains accounting for 5% of all nursing home beds in Norway, 10% in the United States, 13.5% in Sweden, 24% in Canada, and 35% in the United Kingdom.40 There is evidence to support the contention that nursing home chains are associated with poorer quality care. For example, nursing homes that are part of chain organizations have been associated with having lower nurse staffing levels and higher regulatory deficiencies,41 higher regulatory deficiencies for staffing,42 and lower service user satisfaction scores.43 A potential explanatory mechanism for lower quality in for-profit, chain nursing homes is the prioritization of investment returns and shareholder value over other expenditure considerations (e.g., staffing, facilities), which may affect quality.42

We found no evidence of an association of staffing numbers and mean risk rating in the most adjusted analysis. Higher staffing levels, particularly with respect to nurses, have been shown in previous studies to be associated with higher quality in nursing homes,28,29,44 albeit with some authors cautioning against drawing definitive conclusions because of the predominantly cross-sectional nature of the literature and data quality issues. It is possible that there is an interplay between staffing levels and reporting of SI that could be conceived as explaining the lack of association observed. However, because notifications are mandatory and there is evidence of overreporting rather than underreporting in the data, we are not of the opinion that this serves as an explanation.

In relation to bed numbers, there is some evidence from other studies suggesting that larger nursing homes provide poorer quality outcomes compared with smaller ones.25,26 We did not replicate this finding in our results.

In the case of nursing home ownership, the available literature suggests that not-for-profit nursing homes tend to provide higher quality of care compared with for-profit facilities.30 This was not borne out in our findings in the context of non-statutory/statutory ownership of nursing homes. It may be the case that the aforementioned studies used broader or higher-level measures of quality when investigating determinants and that our conceptualization of quality (mean risk rating of SI) produced different findings.

RCF-Disability

Several organizational, environmental, and staffing characteristics related to RCF-Disability and mean risk rating of SI notifications were associated in these analyses, albeit that the magnitude of the associations was small. We found that in the most adjusted model, beds, staff to bed ratio, nurse to bed ratio, staff FTE, provider size, and mean risk rating were all positively associated.

The size of RCF-Disability and impact on quality have been the subject of previous research, particularly with reference to the debate around small community-based services versus larger congregated, institutional-style settings.45 Our finding that larger RCF-Disability (as measured by bed numbers) was associated with higher mean risk rating of SI notifications is consistent with other studies that have reported poorer-quality outcomes in larger settings,46–49 albeit that some of these studies are somewhat dated.

With respect to staffing levels, higher staff to bed ratio and nursing staff to bed ratio were associated with higher mean risk-rating of SI notifications, which is somewhat counterintuitive as one might expect higher staff numbers relative to service users to produce higher quality. Similar to the size of RCF-Disability, it may be the case that both of these staff-related variables are markers of services providing care to people with higher or more complex needs in institutional-style settings. Indeed, congregated settings in Ireland tend to provide care to people who are older and have more severe disabilities.50 This resident profile, in turn, may be a contributory factor to the occurrence of more serious or harmful SI.

Although there is an extensive literature on chains and nursing home quality (see previous discussion), we could find no similar research on chains and disability service quality with which to compare our finding on provider size.

Policy and Practice Implications

Our findings point to a number of modifiable organizational, environmental, and staffing characteristics that have implications for how social care services are structured.

The association of provider size in RCF-Nursing homes and mean risk rating indicates that nursing home chains in Ireland present a higher risk in terms of SI. In the context of extensive expansion of nursing home chains internationally,40 this finding raises important policy implications in terms of how care for the elderly should be structured and provided. Indeed, an overreliance on chains may have consequences for service continuity51 and quality.

The finding that larger RCF-Disability services were associated with higher mean risk rating for SI notifications is yet another indicator that large, congregated settings provide poorer outcomes for people with disabilities living in residential settings.27,46 This has particular relevance for Ireland, where a national policy to phase out such facilities has proceeded much slower than anticipated.52

Strengths and Limitations

A key strength of this study was the use of a large, nationally comprehensive database. This is distinct from other studies in the field that tend to rely on smaller sample sizes. Moreover, we used two years of data to smooth the risk-rating data and diminish the impact of potential spurious reporting in yearly data.

The use of risk rating of SI notifications has the potential to introduce bias in respect of the inspector carrying out the risk rating. Some inspectors may have different risk tolerances or perceptions, and interrater reliability may be less than optimal.53 Risk rating of SI notifications may also be influenced by factors other than the details of the SI, for example, RCF’s prior regulatory performance or frequency/trend observed in recent SI. Nevertheless, risk rating was an appropriate outcome measure to use when compared with others, such as frequency or incidence of SI notifications per RCF, as it more accurately reflects potential impact on service users. Furthermore, the use of mean risk rating in these analyses limits the impact of this type of influence.

Because organizational, environmental, and staffing characteristics often have an impact on quality through their impact on processes, the lack of process characteristics available for analyses could be viewed as a limitation of this work. However, because organizational, environmental, and staffing characteristics can also impact independently and because of the paucity of research in this area, identifying such characteristics is important at this juncture.

CONCLUSIONS

Various modifiable RCF characteristics and severity of SI notifications, as a marker of quality, were associated in this study. The characteristics identified were different for nursing homes and disability centers. Further research is needed to better understand how these organizational, environmental, and staffing characteristics interact with process dimensions of social care to produce quality outcomes. Nonetheless, people should be cognizant of the relationship of these characteristics and severity of SI, when planning residential care.

ACKNOWLEGMENTS

The authors would like to thank the residents of RCF-Disability and RCF-Nursing home who provided input on the development of the Database of Statutory Notifications from Social Care in Ireland and research questions important to them, thus enabling and informing this work.

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