A Case Study in Communication Strategies used for Pressure Ulcer Prevention in a Nursing Home with High IT Sophistication Gregory L. Alexander PhD, RN, FAAN1, Richard Madsen PhD2 1 University of Missouri, Sinclair School of Nursing, Columbia, Missouri, USA; 2 University of Missouri, School of Medicine, Biostatistics Unit Abstract Current strategies for improving the care of millions of elderly people living in nursing homes (NH) include the implementation of information technology (IT). Few studies exist about the implementation of NH IT although there is evidence of increasing NH IT sophistication globally. NH IT sophistication includes a measure of the maturity and diversity of IT used to support resident care, clinical support, and administration. The current paper includes a case study of 1 NH known to have high IT sophistication in the Midwestern USA. The NH was purposively selected from 185 NHs taking part in a statewide evaluation of NH IT sophistication in Missouri. This NH reported the highest IT sophistication among 185 NHs. The research aim was to explore communication strategies for evidence based pressure ulcer preventions in NH IT. Focus group and observational data were collected to assess facilitators and barriers to communicating pressure ulcer preventions. Introduction In 2004, the United States had approximately 16,100 NHs containing 1.7 million beds with an occupancy rate of 86%, representing 1.5 million residents whose average length of stay was just over 2 years(1). Residents’ care is complex. Leading primary medical diagnoses are diseases of the circulatory system (25%), mental disorders (16%), and diseases of the nervous system and sense organs (14%). About 98% of the NH residents received assistance with some activities of daily living, such as bathing, dressing, toileting, transferring and eating; and 51% received assistance with all 5 activities. Just over one-third (35%) had bowel or bladder incontinence. Residents with pressure ulcers (10.7%) ranged from stage 1 (2.6%) to stage 2 or higher (8.1%) (2). Residents in nursing homes in other countries have similar characteristics(3). The Institute of Medicine’s Improving Quality of Long Term Care (2001) cited IT’s important contributions to improved reliability, validity, and timeliness of resident care data used to measure quality(4). Increased attention to medical error and patient safety prompted recommendations to develop IT systems that support clinical decision making, promote data standards, and communicate with other IT systems(5). The purpose of this case study was to explore communication strategies for evidence based pressure ulcer preventions that a NH with high IT sophistication has implemented. Background IT Sophistication Models IT Sophistication describes the information technology and software that support three domains of NH care: Resident Care, Clinical Support, and Administration. The three dimensions of IT Sophistication are: (1) Functional Sophistication, which includes health care delivery processes or activities supported by technology; (2) Technological Sophistication, or the extent of use of hardware/software devices; and (3) Integration Sophistication, which represents the level of internal and external integration among departments and clinical settings inside and outside a facility (6). Figure 1 is a conceptual model illustrating the Current State (low IT Sophistication) and Ideal State (high IT Sophistication) model of NH IT. The model illustrates how IT capabilities, such as clinical decision support systems found in NH with high IT Sophistication, aide in problem recognition and lead to clinical actions that improve resident outcomes. We believe that outcomes will improve as NHs implement these functionalities into bedside care, as providers use them more, and as they are integrated with other systems, such as electronic nursing documentation systems. This conceptual model guided our methodology as we selected a NH with high IT Sophistication and conducted a case study exploring communication strategies used to support implementation of evidence based pressure ulcer preventions. The conceptual model in Figure 1 contrasts NHs that do not have (Current State) the capability to enter resident assessment data into an IT system with NHs that do have such systems (Ideal State)(7). In the Ideal State, any type
NI2012: 11th International Congress on Nursing Informatics 1
of healthcare provider can enter data. The IT algorithms have predetermined clinical criteria, such as “no incontinence” that are compared to data providers enter, such as “resident has increasing incontinence”. When preset criteria do not match resident data, the system generates electronic alerts, such as “skin integrity alert” in the clinical decision support system. The Figure 1 scenario for a skin integrity alert might be turned on for a number of reasons, including when an RN or CNA documents that a resident is comatose, has increased edema, is experiencing increasing incontinent episodes, or when turning repositioning has not been documented. The predetermined criteria can be set by vendors and can often be manipulated by the administrator of the decision support system. When an alert is issued, the system automatically sends a message to the user (RN/CNA) that a potential problem has been identified. This is a prompt for the staff to investigate the problem.
This study is innovative because it will be the first to explore relationships between NH IT Sophistication (i.e., the functionality of IT systems, the extent of their use, and how integrated they are with other care systems) and strategies to communicate evidence based pressure ulcer preventions in NH IT. IT innovations have the potential to change the clinical practice paradigm in NHs by changing the way providers monitor and communicate patient care needs and care processes. This is demonstrated for skin integrity in Figure 1. NH IT administrators could integrate recommended guidelines for pressure ulcer prevention (ex. apply barrier cream for incontinence) into the IT system using automated task lists (another IT capability) to remind RNs/CNAs to practice appropriate resident care. Based on messages staff receive, they can exercise their own clinical decision making based on electronic messages, guidelines, or their own observations; then, staff can choose whether to take clinical action and administrators can monitor these actions. The alert turns off when it is resolved through appropriate documentation. The majority of NHs operates without alerts (Current State), while staff is responsible for making care decisions based upon their own recall and synthesis of vital information. Considering that NH quality problems have been consistent over time and place, it appears that the current state of low IT Sophistication is not working well. The specific aim of this research was to: Explore strategies to communicate evidenced based pressure ulcer pressure ulcer preventions used in a NH with high IT sophistication. Methods This study aim was accomplished by conducting focus groups and staff observations in a NH facility that had responded to a statewide IT sophistication survey during preliminary work. The case study includes a NH facility identified as having the highest reported IT sophistication from 185 nursing homes participating in the statewide survey. All methods were approved by the Universities Institutional Review Board before research was conducted. Since there are 9 scales for each of resident care, clinical support, and administrative activities with each of functional, technological, and integration IT sophistication, we combined the information from these scales to get an overall measure of IT sophistication for all 185 NHs completing the survey. One simple way of combining the information was to take the total of the 9 scales (or equivalently the average). Each scale had a theoretical maximum of 100, so the total had a maximum of 900. An alternate approach was to find a linear combination of the 9 scales that would give maximum variance since a large variance means the scores are spread out and hence
NI2012: 11th International Congress on Nursing Informatics 2
allowed for better discrimination among the homes. One way to do this was to use principal component factor analysis. If the first principal component accounted for a relatively large proportion of the variability contained in the set of 9 scales, then that variable was used as a simple summary measure of the IT information. Alternatively, if the proportion of variability explained is not considered large enough, then the second principal component could be used in addition to the first. A straight forward way to classify NH from highest to lowest IT sophistication was to rank them according to the first principal component and/or according to the total score. An alternate way was to use cluster analysis to find groups of homes that are ‘close’ to each other with respect to some distance measure with respect to a set of variables. The variables could be the 9 subscales themselves or a subset of the principal components. We used these methods to rank the homes from highest to lowest IT sophistication and conducted the case study on the NH with the highest IT sophistication. SAS was used for these statistical analyses. Focus groups were conducted with nurses (RN/LPN), nurses’ assistants, administrators, nursing leadership, and/or IT professionals in the NH with the highest IT sophistication reported. Focus groups consisting of 2-4 voluntary participants were conducted on each shift (days/evenings/nights). All disciplines of direct care staff were recruited by posting colorful fliers in accessible locations in participating facilities informing them of the date, time, and purpose of the interviews. Research staff coordinated meetings with participating nursing home administrators. Incentives including food and drink were offered to participants who participated in focus groups. Attempts were made to recruit staff with diverse opinions and backgrounds (i.e. educational level, job position, and length of employment) to obtain a balanced view of how pressure ulcer prevention measures were being used. Questionnaires were developed to elicit voluntary responses about each employee’s experiences with communication strategies in their facilities, their knowledge of how evidenced-based practices for preventing pressure ulcers are introduced into communication, and how care is prioritized through communication systems. The same questionnaire was used for all focus groups. Specifically, we were interested in evidenced based pressure ulcer preventions implemented in four care categories including risk assessment, skin care practices, mechanical loading and support surfaces, and education. These care categories were developed from an extensive literature review on recommended evidenced based skin care practices completed by the principal investigator. Focus groups were recorded with a digital recorder and transcribed. NVIVO 9.0 software was used to code and analyze focus group data. We used the cluster analysis feature of NVIVO to show relationships among nodes created from the emerging thematic areas discussed by focus group participants. Staff observations were all conducted within a day of focus groups. Staff were observed in dyads including a Registered Nurse/Licensed Practical Nurse and Nurse Assistant ((RN/LPN) and NA) at the facility on each shift. With the assistance of a nursing home administrator, an experienced nurse and NA who had at least one year of NH experience was recruited for observations. All participants were instructed that they could elect not to participate at any time before or during the observations. Dyads consisted of staff assigned to work in tandem with each other during the same shift in the same clinical areas. Observations focused on specific behaviors associated with the communication strategies that direct-care staff used in the facilities. Specifically, investigators looked for communication about prevention strategies for residents at high and low risk for developing pressure ulcers. We used the same care classifications including risk assessment, skin care practices, mechanical loading and support surfaces, and education to code observations for analysis. A mix of observational positioning techniques was used, including moving to different sites within the clinical area and noting the dyad’s caregiving activities. A work design analysis was completed that described staff movements, actions, gestures, and phrases associated with direct care staff as well as the communication strategies relayed about preventive skin-care needs of residents. Observational records were maintained in clinical logs that described events surrounding clinical communication about skin-care planning among direct-care staff. Investigators recorded logs in the field immediately following an observed event using an observational field note guide. Following each observation day, field notes were transcribed. Field notes included: (1) contextual information about the time, place, and direct-care staff involved in the interactions and observations, (2) objective descriptions of observed events and conversations, (3) information about actions, dialogue, and context. Results There were 185 homes completing the IT sophistication survey. Results of the survey are discussed elsewhere(7). Examination of the Eigenvalues for the Principal Component analysis based on the covariance matrix of the 9 subscales tells us that about 64% of the variance in the statewide survey was contained in the first principal component. The total increases to about 75% if the second component was included and 83% when three principal components were included. Direct calculation as well as examination of the coefficients for the first principal
NI2012: 11th International Congress on Nursing Informatics 3
component show that the first principal component differs only slightly from the Total score for all 9 subscales. The correlation between these variables was over 0.99. Hence in terms of selecting the highest and lowest scoring homes, there was not much difference between using either of these two variables. In this set of data there were 5 NHs that were clearly the highest, for this paper we selected the NH with the highest score. In other analysis not reported here we used the clustering technique to select homes with lesser amounts of IT sophistication that were grouped closer. The NH selected for this case study was non-investor owned, was a midsized NH with capacity for 60-120 residents, and located in an urban setting. Total IT sophistication for this facility was 225.7. A total of 6 focus groups with 24 nursing and administrative staff were conducted at this NH. Participating staff reported nearly 6 months of long term care experience up to 25 years. Using NVIVO 9.0 transcribed focus group data was coded into 12 distinct nodes (see figure 2). Staff indicated that communication strategies for skin care practices and risk assessment were closely correlated with usability of the information system being used. Figure 2. Nodes and Cluster Analysis of Focus Group Data Specifically, how information was input into the computer system played a large role in their ability to keep track of resident’s needs. For example, up to date electronic status boards were used by nurses and CNAs to keep track of interventions which were implemented each shift. Status boards at the beginning of each shift were pink and remained pink until the status of the interventions had changed. To track what was being completed by each discipline the status board changed from pink to grey each time a staff member documented an action. Pink items allowed nurses to ensure that proper care was being delivered in a timely manner each shift. Their ability to track whether skin care practices or risk assessments were being completed depended on how information was organized and how it was communicated. In this facility, educational systems used to train staff were important as structured messaging systems were implemented. Furthermore, educational systems were strongly related to security and confidentiality of patient data used by staff. Evolving IT issues that were more distantly related to other thematic areas included patient history and IT department structure. Two investigators conducted approximately 9 hours of observation following Nurse/CNA dyads. A total of 174 observations of staff were documented. A total of 684 individual occurrences of staff incorporating evidence based pressure ulcer prevention measures were documented during observations. An average of 3.9 individual occurrences of pressure ulcer prevention measures for every observation was documented by investigators. The majority of individual occurrences of pressure ulcer prevention practices were documented by observers under Skin Care Practices used and Mechanical Loading and Support Surfaces implemented to reduce pressure on skin. Risk Assessment including the use of a validated risk assessment tools and Structured Educational programs were less often observed. For example, one documented observation included that a CNA was concerned an air mattress was too low and sunk in too much. The observation was coded under risk assessment, skin care, and under mechanical loading and support surfaces. Interventions observed included risk reassessed at periodic intervals, minimization of force and friction applied to skin, protect bony prominences, repositioning patients in bed, and use of pressure reducing device in bed bound individuals. However, documentation only reflected that a resident was on an air mattress and did not fully reflect all interventions that were observed. Discussion A lot can be learned from early adopters of technology. Since most nursing homes have not adopted any forms of technology or are at a very early stage of adoption the time is right to explore how early adopters are using information systems to support care. As part of this exploration, understanding human factors which demonstrate efficiencies, effectiveness, or satisfaction with an information system are critical. The goal of a human factors
NI2012: 11th International Congress on Nursing Informatics 4
approach in a nurse-led system such as NH is to understand how to optimize the interactions between NH staff and the tools they use to accomplish their work (8). In the NH including in this case study, the IT interface had dynamic interactive color features which allowed staff to simultaneously track care delivery as it was happening. The use of these features were ideal because they enabled nurses to assess what was being done for patients without running down the hall to find a nursing assistant to determine if care had been delivered. Staff used their time more efficiently and they were more effective at recognizing care needs. In the current state of information exchange in most NHs care delivery is tracked as nursing staff move up and down hallways. This often results in inefficient use of their time; furthermore, nursing staff are not able to assess care needs as effectively. Tracking care delivery in this facility depended on the timely and proper entry of data by nursing staff. There were several variables that affected this input including how information was organized. In this facility, there was a high accountability to be certain that all interventions which were pink at the beginning of the shift turned to grey by the end of the shift. These dynamic interactions had an effect on the perceptions of the staff that used them. Some staff expressed concerns about role shifts caused by this decision support tool. CNAs in the Current State (see figure 1), typically don’t provide documentation that is a permanent part of the health record. In this facility, CNA documentation was a critical part of the documentation that provided details about resident mobility, incontinence, and other activities of daily living that became part of the permanent record. Perceived role shifts occurred as a result of this change in CNA documentation and perceived responsibility for care delivery. Structured documentation in NH IT systems may not fully capture the essence of all care addressed by nursing care staff. In previous research increasing IT sophistication has been linked with increasing NH quality measures that identify residents at risk for activity of daily living decline(9). It was assumed that increasing documentation by nurse assistants played a role in this correlate. CNAs play an important role in skin care management and prevention. Roles are affected by the types of nursing actions taken and documentation required for the actions. The evaluation of an information system should include how documentation is structured conceptually to fully illustrate the level of care delivered by the nursing staff. Conclusion Exploring the use of IT in NH is critical as nurses try to care for the millions of patients in these types of facilities worldwide. More extensive studies are needed for others to learn from the experiences of early adopters of NH IT. Human factors that assess the effectiveness, efficiencies and satisfaction with IT are important lessons that other NH can learn from. Reference List (1) National Center for Health Statistics. Centers for Disease Control and Prevention FastStats Homepage. http://www.cdc.gov/nchs/fastats/nursingh.htm . 4-15-2010. Ref Type: Electronic Citation (2) Jones AL, Dwyer LL, Bercovitz AR, Strahan GW. The National Nursing Home Survey: 2004 Overview. 13(167). 2009. National Center for Health Statistics.Vital Health Stat. Ref Type: Report (3) Fossum M, Alexander GL, Ehnfors M, Ehrenberg A. Effects of a Computerized Decision Support System on Pressure Ulcers and Malnutrition in Nursing Homes for the Elderly. International Journal of Medical Informatics 2011. (4) Institute of Medicine. Information systems for monitoring quality. In: Wunderlich GS, Kohler PO, editors. Improving the Quality of Long-Term Care. Washington DC: National Academies Press, 2001: 110-134. (5) Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press, 2001. (6) Pare G, Sicotte C. Information technology sophistication in health care: An instrument validation study among Canadian hospitals. International Journal of Medical Informatics 2001; 63:205-223. (7) Alexander GL, Madsen R, Wakefield DS. A Regional Assessment of Information Technology Sophistication in Missouri Nursing Homes. Policy, Politics & Nursing Practice 2010; 11(3):214-225. (8) Alexander GL. Human Factors. In: Virginia Saba, Kathleen McCormick, editors. Essentials of Nursing Informatics. New York: McGraw-Hill, 2011. (9) Alexander GL. Analysis of an integrated clinical decision support system in nursing home clinical information systems. Journal of Gerontological Nursing 2008; 34(2):15-20.
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NI2012: 11th International Congress on Nursing Informatics 1
of healthcare provider can enter data. The IT algorithms have predetermined clinical criteria, such as “no incontinence” that are compared to data providers enter, such as “resident has increasing incontinence”. When preset criteria do not match resident data, the system generates electronic alerts, such as “skin integrity alert” in the clinical decision support system. The Figure 1 scenario for a skin integrity alert might be turned on for a number of reasons, including when an RN or CNA documents that a resident is comatose, has increased edema, is experiencing increasing incontinent episodes, or when turning repositioning has not been documented. The predetermined criteria can be set by vendors and can often be manipulated by the administrator of the decision support system. When an alert is issued, the system automatically sends a message to the user (RN/CNA) that a potential problem has been identified. This is a prompt for the staff to investigate the problem.
This study is innovative because it will be the first to explore relationships between NH IT Sophistication (i.e., the functionality of IT systems, the extent of their use, and how integrated they are with other care systems) and strategies to communicate evidence based pressure ulcer preventions in NH IT. IT innovations have the potential to change the clinical practice paradigm in NHs by changing the way providers monitor and communicate patient care needs and care processes. This is demonstrated for skin integrity in Figure 1. NH IT administrators could integrate recommended guidelines for pressure ulcer prevention (ex. apply barrier cream for incontinence) into the IT system using automated task lists (another IT capability) to remind RNs/CNAs to practice appropriate resident care. Based on messages staff receive, they can exercise their own clinical decision making based on electronic messages, guidelines, or their own observations; then, staff can choose whether to take clinical action and administrators can monitor these actions. The alert turns off when it is resolved through appropriate documentation. The majority of NHs operates without alerts (Current State), while staff is responsible for making care decisions based upon their own recall and synthesis of vital information. Considering that NH quality problems have been consistent over time and place, it appears that the current state of low IT Sophistication is not working well. The specific aim of this research was to: Explore strategies to communicate evidenced based pressure ulcer pressure ulcer preventions used in a NH with high IT sophistication. Methods This study aim was accomplished by conducting focus groups and staff observations in a NH facility that had responded to a statewide IT sophistication survey during preliminary work. The case study includes a NH facility identified as having the highest reported IT sophistication from 185 nursing homes participating in the statewide survey. All methods were approved by the Universities Institutional Review Board before research was conducted. Since there are 9 scales for each of resident care, clinical support, and administrative activities with each of functional, technological, and integration IT sophistication, we combined the information from these scales to get an overall measure of IT sophistication for all 185 NHs completing the survey. One simple way of combining the information was to take the total of the 9 scales (or equivalently the average). Each scale had a theoretical maximum of 100, so the total had a maximum of 900. An alternate approach was to find a linear combination of the 9 scales that would give maximum variance since a large variance means the scores are spread out and hence
NI2012: 11th International Congress on Nursing Informatics 2
allowed for better discrimination among the homes. One way to do this was to use principal component factor analysis. If the first principal component accounted for a relatively large proportion of the variability contained in the set of 9 scales, then that variable was used as a simple summary measure of the IT information. Alternatively, if the proportion of variability explained is not considered large enough, then the second principal component could be used in addition to the first. A straight forward way to classify NH from highest to lowest IT sophistication was to rank them according to the first principal component and/or according to the total score. An alternate way was to use cluster analysis to find groups of homes that are ‘close’ to each other with respect to some distance measure with respect to a set of variables. The variables could be the 9 subscales themselves or a subset of the principal components. We used these methods to rank the homes from highest to lowest IT sophistication and conducted the case study on the NH with the highest IT sophistication. SAS was used for these statistical analyses. Focus groups were conducted with nurses (RN/LPN), nurses’ assistants, administrators, nursing leadership, and/or IT professionals in the NH with the highest IT sophistication reported. Focus groups consisting of 2-4 voluntary participants were conducted on each shift (days/evenings/nights). All disciplines of direct care staff were recruited by posting colorful fliers in accessible locations in participating facilities informing them of the date, time, and purpose of the interviews. Research staff coordinated meetings with participating nursing home administrators. Incentives including food and drink were offered to participants who participated in focus groups. Attempts were made to recruit staff with diverse opinions and backgrounds (i.e. educational level, job position, and length of employment) to obtain a balanced view of how pressure ulcer prevention measures were being used. Questionnaires were developed to elicit voluntary responses about each employee’s experiences with communication strategies in their facilities, their knowledge of how evidenced-based practices for preventing pressure ulcers are introduced into communication, and how care is prioritized through communication systems. The same questionnaire was used for all focus groups. Specifically, we were interested in evidenced based pressure ulcer preventions implemented in four care categories including risk assessment, skin care practices, mechanical loading and support surfaces, and education. These care categories were developed from an extensive literature review on recommended evidenced based skin care practices completed by the principal investigator. Focus groups were recorded with a digital recorder and transcribed. NVIVO 9.0 software was used to code and analyze focus group data. We used the cluster analysis feature of NVIVO to show relationships among nodes created from the emerging thematic areas discussed by focus group participants. Staff observations were all conducted within a day of focus groups. Staff were observed in dyads including a Registered Nurse/Licensed Practical Nurse and Nurse Assistant ((RN/LPN) and NA) at the facility on each shift. With the assistance of a nursing home administrator, an experienced nurse and NA who had at least one year of NH experience was recruited for observations. All participants were instructed that they could elect not to participate at any time before or during the observations. Dyads consisted of staff assigned to work in tandem with each other during the same shift in the same clinical areas. Observations focused on specific behaviors associated with the communication strategies that direct-care staff used in the facilities. Specifically, investigators looked for communication about prevention strategies for residents at high and low risk for developing pressure ulcers. We used the same care classifications including risk assessment, skin care practices, mechanical loading and support surfaces, and education to code observations for analysis. A mix of observational positioning techniques was used, including moving to different sites within the clinical area and noting the dyad’s caregiving activities. A work design analysis was completed that described staff movements, actions, gestures, and phrases associated with direct care staff as well as the communication strategies relayed about preventive skin-care needs of residents. Observational records were maintained in clinical logs that described events surrounding clinical communication about skin-care planning among direct-care staff. Investigators recorded logs in the field immediately following an observed event using an observational field note guide. Following each observation day, field notes were transcribed. Field notes included: (1) contextual information about the time, place, and direct-care staff involved in the interactions and observations, (2) objective descriptions of observed events and conversations, (3) information about actions, dialogue, and context. Results There were 185 homes completing the IT sophistication survey. Results of the survey are discussed elsewhere(7). Examination of the Eigenvalues for the Principal Component analysis based on the covariance matrix of the 9 subscales tells us that about 64% of the variance in the statewide survey was contained in the first principal component. The total increases to about 75% if the second component was included and 83% when three principal components were included. Direct calculation as well as examination of the coefficients for the first principal
NI2012: 11th International Congress on Nursing Informatics 3
component show that the first principal component differs only slightly from the Total score for all 9 subscales. The correlation between these variables was over 0.99. Hence in terms of selecting the highest and lowest scoring homes, there was not much difference between using either of these two variables. In this set of data there were 5 NHs that were clearly the highest, for this paper we selected the NH with the highest score. In other analysis not reported here we used the clustering technique to select homes with lesser amounts of IT sophistication that were grouped closer. The NH selected for this case study was non-investor owned, was a midsized NH with capacity for 60-120 residents, and located in an urban setting. Total IT sophistication for this facility was 225.7. A total of 6 focus groups with 24 nursing and administrative staff were conducted at this NH. Participating staff reported nearly 6 months of long term care experience up to 25 years. Using NVIVO 9.0 transcribed focus group data was coded into 12 distinct nodes (see figure 2). Staff indicated that communication strategies for skin care practices and risk assessment were closely correlated with usability of the information system being used. Figure 2. Nodes and Cluster Analysis of Focus Group Data Specifically, how information was input into the computer system played a large role in their ability to keep track of resident’s needs. For example, up to date electronic status boards were used by nurses and CNAs to keep track of interventions which were implemented each shift. Status boards at the beginning of each shift were pink and remained pink until the status of the interventions had changed. To track what was being completed by each discipline the status board changed from pink to grey each time a staff member documented an action. Pink items allowed nurses to ensure that proper care was being delivered in a timely manner each shift. Their ability to track whether skin care practices or risk assessments were being completed depended on how information was organized and how it was communicated. In this facility, educational systems used to train staff were important as structured messaging systems were implemented. Furthermore, educational systems were strongly related to security and confidentiality of patient data used by staff. Evolving IT issues that were more distantly related to other thematic areas included patient history and IT department structure. Two investigators conducted approximately 9 hours of observation following Nurse/CNA dyads. A total of 174 observations of staff were documented. A total of 684 individual occurrences of staff incorporating evidence based pressure ulcer prevention measures were documented during observations. An average of 3.9 individual occurrences of pressure ulcer prevention measures for every observation was documented by investigators. The majority of individual occurrences of pressure ulcer prevention practices were documented by observers under Skin Care Practices used and Mechanical Loading and Support Surfaces implemented to reduce pressure on skin. Risk Assessment including the use of a validated risk assessment tools and Structured Educational programs were less often observed. For example, one documented observation included that a CNA was concerned an air mattress was too low and sunk in too much. The observation was coded under risk assessment, skin care, and under mechanical loading and support surfaces. Interventions observed included risk reassessed at periodic intervals, minimization of force and friction applied to skin, protect bony prominences, repositioning patients in bed, and use of pressure reducing device in bed bound individuals. However, documentation only reflected that a resident was on an air mattress and did not fully reflect all interventions that were observed. Discussion A lot can be learned from early adopters of technology. Since most nursing homes have not adopted any forms of technology or are at a very early stage of adoption the time is right to explore how early adopters are using information systems to support care. As part of this exploration, understanding human factors which demonstrate efficiencies, effectiveness, or satisfaction with an information system are critical. The goal of a human factors
NI2012: 11th International Congress on Nursing Informatics 4
approach in a nurse-led system such as NH is to understand how to optimize the interactions between NH staff and the tools they use to accomplish their work (8). In the NH including in this case study, the IT interface had dynamic interactive color features which allowed staff to simultaneously track care delivery as it was happening. The use of these features were ideal because they enabled nurses to assess what was being done for patients without running down the hall to find a nursing assistant to determine if care had been delivered. Staff used their time more efficiently and they were more effective at recognizing care needs. In the current state of information exchange in most NHs care delivery is tracked as nursing staff move up and down hallways. This often results in inefficient use of their time; furthermore, nursing staff are not able to assess care needs as effectively. Tracking care delivery in this facility depended on the timely and proper entry of data by nursing staff. There were several variables that affected this input including how information was organized. In this facility, there was a high accountability to be certain that all interventions which were pink at the beginning of the shift turned to grey by the end of the shift. These dynamic interactions had an effect on the perceptions of the staff that used them. Some staff expressed concerns about role shifts caused by this decision support tool. CNAs in the Current State (see figure 1), typically don’t provide documentation that is a permanent part of the health record. In this facility, CNA documentation was a critical part of the documentation that provided details about resident mobility, incontinence, and other activities of daily living that became part of the permanent record. Perceived role shifts occurred as a result of this change in CNA documentation and perceived responsibility for care delivery. Structured documentation in NH IT systems may not fully capture the essence of all care addressed by nursing care staff. In previous research increasing IT sophistication has been linked with increasing NH quality measures that identify residents at risk for activity of daily living decline(9). It was assumed that increasing documentation by nurse assistants played a role in this correlate. CNAs play an important role in skin care management and prevention. Roles are affected by the types of nursing actions taken and documentation required for the actions. The evaluation of an information system should include how documentation is structured conceptually to fully illustrate the level of care delivered by the nursing staff. Conclusion Exploring the use of IT in NH is critical as nurses try to care for the millions of patients in these types of facilities worldwide. More extensive studies are needed for others to learn from the experiences of early adopters of NH IT. Human factors that assess the effectiveness, efficiencies and satisfaction with IT are important lessons that other NH can learn from. Reference List (1) National Center for Health Statistics. Centers for Disease Control and Prevention FastStats Homepage. http://www.cdc.gov/nchs/fastats/nursingh.htm . 4-15-2010. Ref Type: Electronic Citation (2) Jones AL, Dwyer LL, Bercovitz AR, Strahan GW. The National Nursing Home Survey: 2004 Overview. 13(167). 2009. National Center for Health Statistics.Vital Health Stat. Ref Type: Report (3) Fossum M, Alexander GL, Ehnfors M, Ehrenberg A. Effects of a Computerized Decision Support System on Pressure Ulcers and Malnutrition in Nursing Homes for the Elderly. International Journal of Medical Informatics 2011. (4) Institute of Medicine. Information systems for monitoring quality. In: Wunderlich GS, Kohler PO, editors. Improving the Quality of Long-Term Care. Washington DC: National Academies Press, 2001: 110-134. (5) Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press, 2001. (6) Pare G, Sicotte C. Information technology sophistication in health care: An instrument validation study among Canadian hospitals. International Journal of Medical Informatics 2001; 63:205-223. (7) Alexander GL, Madsen R, Wakefield DS. A Regional Assessment of Information Technology Sophistication in Missouri Nursing Homes. Policy, Politics & Nursing Practice 2010; 11(3):214-225. (8) Alexander GL. Human Factors. In: Virginia Saba, Kathleen McCormick, editors. Essentials of Nursing Informatics. New York: McGraw-Hill, 2011. (9) Alexander GL. Analysis of an integrated clinical decision support system in nursing home clinical information systems. Journal of Gerontological Nursing 2008; 34(2):15-20.
NI2012: 11th International Congress on Nursing Informatics 5
