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Better patient outcomes are often achieved through effective surveillance, a primary function of nurses. The purpose of this paper is to define, operationalize, measure, and evaluate the nurse surveillance capacity of hospitals. Nurse surveillance capacity is defined as the organizational features that enhance or weaken nurse surveillance. It includes a set of registered nurses (staffing, education, expertise, experience) and nurse practice environment characteristics.Empirical referents were extracted from existing survey data from 9,232 nurses in 174 hospitals. Using a ranking methodology, a Hospital Nurse Surveillance Capacity Profile was created for each hospital. Greater nurse surveillance capacity was significantly associated with a better quality of care and fewer adverse events. The profile may assist administrators to improve nurse surveillance and patient outcomes.Surveillance has multiple meanings in health care. The most familiar is population-based monitoring of health indicators, such as tracking infectious disease vectors or documenting increasing obesity rates in the general population. Nurses may be involved in population health surveillance through activities such as blood pressure and weight screenings at health fairs and in epidemiological studies.There is another less frequently used meaning of surveillance that involves the health care of individuals. Dougherty (1999) defined this type of surveillance as “the application of behavioral and cognitive processes in the systematic collection of information used to make judgments and predictions about a person’s health status”.In addition, in the Nursing Interventions Classification (NIC), surveillance is defined as “the purposeful and ongoing acquisition, interpretation, and synthesis of patient data for clinical decision-making” (McCloskey & Bulechek, 1996).A conceptualization has not been developed, however, that captures the essence of nurse surveillance as a cumulative and temporal process, or describes a healthcare organization’s capacity for excellent nurse surveillance.The Quality Health Outcomes Model (QHOM; Mitchell, Ferketich, & Jennings, 1998) provided a theoretical base for framing the examination of nurse surveillance and nurse surveillance capacity. In the model, system and patient characteristics have a direct effect on outcomes; the effect of an intervention on outcomes is mediated by both system and patient characteristics. In the context of our study, nurse surveillance capacity has a direct effect on outcomes, and the effect of nurse surveillance on outcomes is mediated by nurse surveillance capacity and patient characteristics. The system characteristic in our study is nurse surveillance capacity (i.e., RN characteristics and the nurse practice environment) that influences the intervention of nurse surveillance. A direct measure of nurse surveillance is difficult to obtain; therefore our study does not show how the relationship between the nurse surveillance and outcomes could be mediated by system characteristics. Rather, the focus of this study was on the direct relationship between nurse surveillance capacity and outcomes, including quality of care. Patient characteristics, such as the severity of illness at admission, also are theorized to affect patient outcomes. However, the inclusion of patient characteristics was not possible because patient-level data were not collected in the survey.Nurse Surveillance: An InterventionNurse surveillance is a process through which nurses monitor, evaluate, and act upon emerging indicators of a patient’s change in status. The components of this process include ongoing observation and assessment, recognition, interpretation of clinical data, and decision-making.Ongoing observation and assessmentTemporality is a critical component in the examination of surveillance (Dougherty, 1999). According to Dougherty, surveillance differs from assessment in that surveillance is an ongoing practice that occurs over time, whereas assessment frequently is referred to as a one-time event. The process of ongoing observation and data collection in nursing includes physical and mental examinations, and vigilant watching for physiological or behavioral changes using sensory data, such as seeing and hearing, during interactions with patients (Zeitz, 2005).Technological devices, such as electronic monitors, may aid nurses in this function as well. Nurse surveillance also includes the ongoing monitoring of laboratory findings and medications, including side effects and drug interactions (Benson & Briscoe, 2003). As a consequence of surveillance, changes in patient status are identified either as presenting a risk or as evidence of desired responses to treatment.RecognitionAn integral piece of surveillance is the nurse’s ability to recognize patient conditions that deviate from baseline measurements or parameters of interest. The parameters of interest are established through the initial assessment of the patient (Dougherty, 1999). Several indicators serve as markers for recognizable change in patient status including vital signs, neurological and mental status, cardiac and respiratory functioning, and laboratory results (IOM, 2004). The ability to recognize and “read the situation” requires professional knowledge, expertise, and experience. This skill is facilitated by a nurse’s ability to recall previous experiences of similar situations and respond (Benner & Tanner, 1987).InterpretationAfter observing and recognizing an alteration, the nurse interprets and synthesizes this information in the context of the patient and the environment, relying heavily upon critical thinking and clinical judgment. Critical thinking entails an attitude of skeptical inquiry as well as intellectual ability (Kenney, 1995). Tanner, Benner, Chesla, and Gordon (1993) defined clinical judgment as to the application of formal knowledge and theory to nurses’ understanding of patients in the context of a given situation.Decision-makingAfter collecting and interpreting patient data, the nurse makes a decision to continue monitoring or act upon indicators of change in a patient’s status. Nurses act upon changes in a patient’s status by modifying the plan of care, communicating with other providers, or mobilizing resources. Multiple researchers (Kramer et al., 2007; Kramer & Schmalenberg, 2004a; Pearson et al., 2000) have cited the importance of nurses’ independent decision making to the quality of care that patients receive. Often, decisions may be influenced by organizational and environmental factors, such as resource availability and the practice environment.Cumulative and Temporal Aspects of SurveillanceAlthough surveillance is considered to be a nursing intervention provided by a single nurse on behalf of a single patient, in reality, individual patients are cared for in most contexts by multiple nurses over time. Thus, nurse surveillance as a nursing intervention has cumulative and temporal aspects.Associating the effectiveness of surveillance by an individual nurse with the outcomes of an individual patient in most contemporary health care settings is not possible because nurse surveillance is cumulative across nurses and overtime. Benner (1984, p. 126) illustrated this in her qualitative research reported in From Novice to Expert: a charge nurse making rounds enters a room and immediately observes a lidocaine intravenous drip using a macro- rather than a micro-drip. Nurses on two previous shifts, including a float nurse and a new graduate, had failed to associate the patient’s lethargy to over-medication. The charge nurse, whose surveillance was excellent, instituted a rescue attempt by turning the drip off, but the collective surveillance across multiple nurses over time contributed to the patient’s subsequent cardiac arrest and death. Thus, nurse surveillance is a collective effort of interventions delivered by multiple nurses over time, as well as interventions by individual nurses.It is equally difficult to measure individual and collective nurse surveillance. However, an organizational level indicator of nurse surveillance capacity across nurses and overtime would offer a metric with the potential to guide decisions that could improve surveillance, quality of care, and patient outcomes. A metric such as a nurse surveillance capacity also would be valuable to build research evidence for administrators.Nurse Surveillance CapacityNurse surveillance capacity is defined as the organizational features that enhance or weaken nurse surveillance. Nurse surveillance capacity includes RN characteristics (staffing, education, clinical expertise, and years of experience), and the nurse practice environment. The concurrent evaluation of each of these characteristics comprises the Hospital Nurse Surveillance Capacity Profile.StaffingRegistered nurse staffing has been associated empirically with patient outcomes (Aiken, Clarke, Sloane, Sochalski, & Silber, 2002; Mark, Harless, McCue, & Xu, 2004; Needleman, Buerhaus, Mattke, Stewart, & Zelevinsky, 2002). For example, Aiken, Clarke, Sloane, Sochalski, et al (2002) found an increased risk of 30-day mortality, as well as an increased risk of failure-to-rescue, for surgical patients in hospitals with high patient-to-nurse ratios. Therefore, “the effectiveness of nurse surveillance is influenced by the number of registered nurses available to assess patients on an ongoing basis” (Aiken, Clarke, Sloane, Sochalski, et al., 2002, p. 1992).EducationIn addition to staffing, researchers have focused on the educational background of nurses as a predictor of patient outcomes (Aiken, Clarke, Cheung, Sloane, & Silber, 2003; Estabrooks, Midodzi, Cummings, Ricker, & Giovannetti, 2005; Tourangeau et al., 2007). Aiken and colleagues (2003) found significantly lower rates of 30-day mortality and failure-to-rescue among surgical patients in hospitals with higher proportions of nurses who had earned at least a baccalaureate degree in nursing. Aiken’s findings were supported in two studies in Canada (Estabrooks et al.; Tourangeau et al., 2007). Researchers hypothesize that baccalaureate preparation has a positive association with nurses’ critical thinking and clinical judgment skills, which are essential to the surveillance of patients, both in terms of risk for adverse events and in the evaluation of therapies (Aiken et al., 2003; Young, Lehrer, & White, 1991).Clinical expertiseIn an influential work, Benner & Tanner (1987) explored the relationship between expertise and nurses’ practice style and demonstrated how expert nurses develop intuition - a powerful feature of the surveillance process. Intuition is defined as “understanding without rationale” (Benner & Tanner, p. 23). Expert nurses are able to recognize patterns and relate current clinical situations to past experience, integrate the knowledge of the patient’s disease with contextual knowledge about the patient, and are skilled in their specialty areas.Expert nurses also practice deliberative rationality-the capacity to view a clinical scenario from different perspectives; they also possess a sense of salience- the ability to identify the most pertinent observations in a complex assessment (Benner & Tanner). Therefore, expert nurses are able to immediately detect changes in a patient’s condition and intervene to prevent adverse occurrences (Christensen & Hewitt-Taylor, 2006; Houser, 2003).Years of experienceExperience is necessary for gaining expertise, but the two are not necessarily interchangeable (Christensen & Hewitt-Taylor, 2006; Houser, 2003). The number of years of experience, however, provides exposure to different patient conditions and clinical scenarios that contribute to the development of knowledge, technical skills, and critical thinking (Benner, 1984; Newman, 1990).Research that links experience to patient outcomes is scarce; however, existing findings are promising. For example, Tourangeau, Giovannetti, Tu, and Wood (2002) found that each additional year of nurse experience was associated with six fewer patient deaths for every 1000 patients discharged from urban community hospitals. In another study, units with more experienced nurses reported lower rates of medication errors and adverse events (Blegen, Vaughn, & Goode, 2001).Nurse practice environmentThe nurse practice environment is defined as “the organizational characteristics of a work setting that facilitate or constrain professional nursing practice” (Lake, 2002, p. 178). Several instruments have been developed to measure the nurse practice environment.One of these, the Practice Environment Scale of the Nursing Work Index (PES-NWI; Lake, 2002), is used to measure elements that are critical to nurse surveillance. Furthermore, the PES-NWI has been endorsed by the National Quality Forum (NQF) as a nursing-sensitive standard measure for inpatient care (NQF, 2004).The five domains of the PES-NWI are:Nurse Participation in Hospital Affairs;Nursing Foundations for Quality of Care;Nurse Manager Ability,Leadership and Support of Nurses;Staffing and Resource Adequacy; andCollegial Nurse-Physician Relations (Lake, 2002).Nurse participation in hospital affairs is not an obvious component of surveillance. However, in hospitals where nurses are able to influence administrative decisions and policies, nurses are likely to be more efficient in their practice (Aiken, Lake, Sochalski, & Sloane, 1997).Nursing foundations for quality care, such as patient assignments that promote continuity of care, are conducive to surveillance by enhancing the accumulation of knowledge about a patient. Job performance and productivity, including surveillance, depending on the support and ability of the nurse manager (Kramer, Schmalenberg, & Maguire, 2004).Nurses need the staffing support to have adequate time to spend with their patients to perform surveillance, as well as adequate resources available to them to implement necessary interventions (Laschinger & Lieter, 2006; McCusker, Dendukuri, Cardinal, Laplante, & Bambonye, 2004). Further, collegial relationships with physicians are essential to effective surveillance through the exchange of information vital to the patient’s clinical condition (Baggs et al., 1999; Kramer & Schmalenberg, 2004b).Nurse Surveillance and OutcomesBetter nurse surveillance is considered to be the link between better RN staffing/education and the prevention of mortality and failure-to-rescue in surgical patients (Aiken et al., 2003; Aiken, Clarke, Sloane, Sochalski, et al., 2002; Clarke & Aiken, 2003). With the elements of nurse surveillance capacity in place, nurses are better able to perform adequate surveillance of patients and initiate a timely response when a complication or adverse event is detected.Therefore, theoretically, multiple adverse outcomes may be used to assess the effectiveness of hospital nurse surveillance capacity, including mortality and failure-to-rescue. We posit that nurse surveillance capacity has the same relevance for all patient populations and non-mortality outcomes. Other outcomes of nurse surveillance capacity may include quality of care and adverse events, such as falls and nosocomial infections.Data SourceThis study was a secondary analysis of data derived from a 50% random sample survey of Pennsylvania RNs that was conducted in 1999. The survey response rate was 52%, for a total of 43,329 RNs (Aiken et al., 2001). The survey was developed to examine the relationships between nurse staffing, work environment, and patient outcomes (Aiken, Clarke, & Sloane, 2002). The survey contained questions about hospital work environments, workload, workplace safety, quality of care assessments, demographics, education, and experience. Data reflecting individual patient characteristics were not collected in the survey.SampleOf the 43,329 respondents, 13,204 nurses indicated they worked in one of the 210 acute care hospitals in the state. Nurses were included in the final sample for this study if they identified their primary position as a staff nurse working in acute care (excluding the emergency room). Hospitals were included in the sample that had a sufficient number of respondents to assure reliable aggregate values of surveillance capacity variables, as described elsewhere (Aiken, Clarke, Sloane, Sochalski, et al., 2002). An average of 60 nurse respondents from each hospital completed questionnaires. One-half of the hospitals had more than 50 nurse respondents and over 80% of the hospitals had more than 25 nurse respondents. The final sample for this analysis consisted of 9,232 RNs in 174 hospitals in the state of Pennsylvania.MeasuresEmpirical referents were extracted from the Pennsylvania nurse survey to operationalize nurse surveillance capacity. A Hospital Nurse Surveillance Capacity Profile was constructed for each hospital by ranking hospitals on a set of RN characteristics (staffing, education, clinical expertise, and years of experience) and the nurse practice environment. An aggregate measure of hospital nurse surveillance capacity was constructed by calculating a hospital’s average ranking across indicators. Nurse-assessed quality of care and two adverse event variables (nosocomial infections and patient falls with injuries) were the outcomes in this study.StaffingNurses were asked to provide the number of patients cared for on their last shift. The mean number of patients cared for was calculated across all staff nurses within a hospital who reported caring for at least 1 but no more than 20 patients on their last shift. Aiken, Clarke, Sloane, Sochalski, and Silber (2002) considered this measure of staffing to be more accurate than administrative database sources. Harless and Mark (2006) discussed the bias introduced into staffing estimates when using administrative financial data to predict staffing allocation levels.EducationNurses were asked to provide their highest level of education in nursing. Respondents chose from diploma, associate degree, baccalaureate degree, master’s degree, or other. The education variable was operationalized as the proportion of staff nurse respondents within each hospital holding a baccalaureate degree or higher.Clinical expertiseNurses were asked to describe their clinical nursing expertise by choosing from one of the following response categories defined by Benner (1984): advanced beginner, competent, proficient, and expert. Responses were coded 1 to 4 respectively. The clinical expertise variable was calculated as the mean expertise of nurse respondents in each hospital.Years of experienceNurses were asked to provide the number of years they had worked as an RN. The experience variable was calculated at the hospital-level as the mean number of years of RN experience.Nurse practice environmentThe nurse practice environment was measured using the PES-NWI (Lake, 2002). The PES-NWI includes 31 items that use a 4-point Likert scale (strongly agree, somewhat agree, somewhat disagree, and strongly disagree) to assess nurses’ perceptions of the presence of organizational characteristics in their hospitals.A mean score for each of the five subscales was calculated at the hospital-level from the hospital mean of the individual items composing each subscale (Rousseau, 1985; Verran, Gerber, & Milton, 1995).The reliability of the five subscales was examined at the hospital-level by calculating the intraclass correlation coefficient (ICC (1, k)) across hospitals using a minimum criterion of .60 (Glick, 1985).All five subscales demonstrated acceptable reliability at the hospital-level with ICC (1, k)s ranging from a low of .67 for the Collegial Nurse-Physician Relations subscale to a high of .89 for the Participation in Hospital Affairs subscale. Internal consistency coefficients (Cronbach’s alphas) for the five subscales ranged from .78 to .85.Discriminate validity of the PES-NWI has been demonstrated by its ability to detect differences in the nurse practice environments of a magnet and non-magnet hospitals (Lake & Friese, 2006).Quality of careNurses were asked to rate the quality of nursing care delivered to patients on their unit using a 4-point Likert scale of excellent, good, fair, and poor. The reliability of the quality of care variable was examined at the aggregate level by calculating the ICC (1, k) across hospitals. The ICC (1, k) for quality of care was .73. Responses were collapsed into categories of poor/fair and good/excellent care to examine associations with the nurse surveillance capacity rankings.Adverse eventsNurses were asked to report how often two different adverse events, nosocomial infections, and patient falls with injuries, occurred involving their patients over the past year. The frequency of adverse events was measured using a 4-point Likert-type scale of never, rarely, occasionally, or frequently. The reliability of the adverse event measures at the aggregate level was examined by calculating the ICC (1, k) across hospitals.The ICC (1, k)s for nosocomial infections and patient falls with injuries were .73 and .71, respectively. Responses were collapsed into categories of never/rarely and occasionally/frequently to examine associations with the nurse surveillance capacity rankings.Data AnalysisThe purposes of the data analysis were to describe hospitals’ nurse surveillance capacity, to rank hospitals by nurse surveillance capacity, and to associate hospitals’ average ranking with quality of care indicators. Individual nurse responses were examined to assess demographics. Nurse responses were then aggregated to the hospital-level to create the nurse surveillance capacity indicators. Distributions for the aggregated variables were calculated.To create a Hospital Nurse Surveillance Capacity Profile, the hospitals first were ranked on each nurse surveillance capacity indicator so that they rank on each indicator reflected the hospital’s placement among all hospitals. A profile was developed to display hospital ranks by deciles for clarity of comparison, with 1 as the lowest and 10 as the highest decile. A Hospital Nurse Surveillance Capacity Profile was created for each of the 174 represented hospitals.Hospitals’ overall nurse surveillance capacity was then calculated as the mean ranking across all nine nurse surveillance capacity indicators. Finally, hospitals’ overall nurse surveillance capacities were ordered into deciles, with 1 as the lowest and 10 as the highest decile. One hospital profile from the overall highest decile and another from the lowest were selected to illustrate and to contrast a highly ranked hospital and its consistent performance across indicators with a low ranked hospital.To associate hospitals’ rankings with quality of care indicators, outcomes of hospitals in the highest and lowest deciles of overall nurse surveillance capacity ranking were compared. Nurse responses were aggregated to the hospital-level to create the outcome measures.Same-source bias was of concern as the nurse survey was used to measure the independent and dependent variables. Therefore, a split-sample approach was used to test the robustness of the estimates. In every hospital, a random half of the nurses’ responses were aggregated for the organizational measures. The other half was aggregated for the outcome measures, and the analysis was repeated.FindingsNurse Respondent DemographicsDemographics of the nurse respondents were examined. Nearly all respondents were female (94%). The average respondent was 39 years of age. The majority of the nurses worked on a medical/surgical unit (38%); about a quarter of the respondents (24%) worked in intensive care.Nurse Surveillance Capacity DistributionsAverage staffing across all hospitals was just over 5 patients per nurse. On average, one-third of the nurses within a hospital held at least a baccalaureate degree had over 13 years of experience as an RN and rated themselves as competent to proficient in their clinical expertise.A low proportion of hospitals (1 in10) had a majority of nurses who rated their practice as proficient or expert (average expertise ≥3.0). Hsubscale hospitals tended to score highest on the Nursing Foundations for Quality of Care of the PES-NWI; the lowest scored subscale was Staffing and Resource Adequacy. The Quality Health Outcomes Model (QHOM; Mitchell, Ferketich, & Jennings, 1998) provided a theoretical base for framing the examination of nurse surveillance and nurse surveillance capacity.In the model, system and patient characteristics have a direct effect on outcomes; the effect of an intervention on outcomes is mediated by both system and patient characteristics. In the context of our study, nurse surveillance capacity has a direct effect on outcomes, and the effect of nurse surveillance on outcomes is mediated by nurse surveillance capacity and patient characteristics. The system characteristic in our study is nurse surveillance capacity (i.e., RN characteristics and the nurse practice environment) that influences the intervention of nurse surveillance.A direct measure of nurse surveillance is difficult to obtain; therefore our study does not show how the relationship between the nurse surveillance and outcomes could be mediated by system characteristics. Rather, the focus of this study was on the direct relationship between nurse surveillance capacity and outcomes, including quality of care. Patient characteristics, such as the severity of illness at admission, also are theorized to affect patient outcomes. However, the inclusion of patient characteristics was not possible because patient-level data were not collected in the survey.Nurse Surveillance: An InterventionNurse surveillance is a process through which nurses monitor, evaluate, and act upon emerging indicators of a patient’s change in status. The components of this process include ongoing observation and assessment, recognition, interpretation of clinical data, and decision-making.Ongoing observation and assessmentTemporality is a critical component in the examination of surveillance (Dougherty, 1999). According to Dougherty, surveillance differs from assessment in that surveillance is an ongoing practice that occurs over time, whereas assessment frequently is referred to as a one-time event.The process of ongoing observation and data collection in nursing includes physical and mental examinations, and vigilant watching for physiological or behavioral changes using sensory data, such as seeing and hearing, during interactions with patients (Zeitz, 2005).Technological devices, such as electronic monitors, may aid nurses in this function as well. Nurse surveillance also includes the ongoing monitoring of laboratory findings and medications, including side effects and drug interactions (Benson & Briscoe, 2003). As a consequence of surveillance, changes in patient status are identified either as presenting a risk or as evidence of desired responses to treatment.RecognitionAn integral piece of surveillance is the nurse’s ability to recognize patient conditions that deviate from baseline measurements or parameters of interest. The parameters of interest are established through the initial assessment of the patient (Dougherty, 1999).Several indicators serve as markers for recognizable change in patient status including vital signs, neurological and mental status, cardiac and respiratory functioning, and laboratory results (IOM, 2004). The ability to recognize and “read the situation” requires professional knowledge, expertise, and experience. This skill is facilitated by a nurse’s ability to recall previous experiences of similar situations and respond (Benner & Tanner, 1987).InterpretationAfter observing and recognizing an alteration, the nurse interprets and synthesizes this information in the context of the patient and the environment, relying heavily upon critical thinking and clinical judgment.Critical thinking entails an attitude of skeptical inquiry as well as intellectual ability (Kenney, 1995). Tanner, Benner, Chesla, and Gordon (1993) defined clinical judgment as to the application of formal knowledge and theory to nurses’ understanding of patients in the context of a given situation.Decision-makingAfter collecting and interpreting patient data, the nurse makes a decision to continue monitoring or act upon indicators of change in a patient’s status. Nurses act upon changes in a patient’s status by modifying the plan of care, communicating with other providers, or mobilizing resources.Multiple researchers (Kramer et al., 2007; Kramer & Schmalenberg, 2004a; Pearson et al., 2000) have cited the importance of nurses’ independent decision making to the quality of care that patients receive. Often, decisions may be influenced by organizational and environmental factors, such as resource availability and the practice environment.Cumulative and Temporal Aspects of SurveillanceAlthough surveillance is considered to be a nursing intervention provided by a single nurse on behalf of a single patient, in reality, individual patients are cared for in most contexts by multiple nurses over time. Thus, nurse surveillance as a nursing intervention has cumulative and temporal aspects.Associating the effectiveness of surveillance by an individual nurse with the outcomes of an individual patient in most contemporary health care settings is not possible because nurse surveillance is cumulative across nurses and overtime. Benner (1984, p. 126) illustrated this in her qualitative research reported in From Novice to Expert: a charge nurse making rounds enters a room and immediately observes a lidocaine intravenous drip using a macro- rather than a micro-drip.d fai Nure the patient’s lethargy to over-medication.The charge nurse, whose on two previous shifts, including a float nurse and a new graduate, haled to associate surveillance was excellent, instituted a rescue attempt by turning the drip off, but the collective surveillance across multiple nurses over time contributed to the patient’s subsequent cardiac arrest and death. Thus, nurse surveillance is a collective effort of interventions delivered by multiple nurses over time, as well as interventions by individual nurses.It is equally difficult to measure individual and collective nurse surveillance. However, an organizational level indicator of nurse surveillance capacity across nurses and overtime would offer a metric with the potential to guide decisions that could improve surveillance, quality of care, and patient outcomes. A metric such as nurse surveillance capacity also would be valuable to build research evidence for administrators.Nurse Surveillance CapacityNurse surveillance capacity is defined as the organizational features that enhance or weaken nurse surveillance. Nurse surveillance capacity includes RN characteristics (staffing, education, clinical expertise, and years of experience), and the nurse practice environment. The concurrent evaluation of each of these characteristics comprises the Hospital Nurse Surveillance Capacity Profile.StaffingRegistered nurse staffing has been associated empirically with patient outcomes (Aiken, Clarke, Sloane, Sochalski, & Silber, 2002; Mark, Harless, McCue, & Xu, 2004; Needleman, Buerhaus, Mattke, Stewart, & Zelevinsky, 2002). For example, Aiken, Clarke, Sloane, Sochalski, et al (2002) found an increased risk of 30-day mortality, as well as an increased risk of failure-to-rescue, for surgical patients in hospitals with high patient-to-nurse ratios. Therefore, “the effectiveness of nurse surveillance is influenced by the number of registered nurses available to assess patients on an ongoing basis” (Aiken, Clarke, Sloane, Sochalski, et al., 2002, p. 1992).EducationIn addition to staffing, researchers have focused on the educational background of nurses as a predictor of patient outcomes (Aiken, Clarke, Cheung, Sloane, & Silber, 2003; Estabrooks, Midodzi, Cummings, Ricker, & Giovannetti, 2005; Tourangeau et al., 2007). Aiken and colleagues (2003) found significantly lower rates of 30-day mortality and failure-to-rescue among surgical patients in hospitals with higher proportions of nurses who had earned at least a baccalaureate degree in nursing.Aiken’s findings were supported in two studies in Canada (Estabrooks et al.; Tourangeau et al., 2007). Researchers hypothesize that baccalaureate preparation has a positive association with nurses’ critical thinking and clinical judgment skills, which are essential to the surveillance of patients, both in terms of risk for adverse events and in the evaluation of therapies (Aiken et al., 2003; Young, Lehrer, & White, 1991).Clinical expertiseIn an influential work, Benner & Tanner (1987) explored the relationship between expertise and nurses’ practice style and demonstrated how expert nurses develop intuition - a powerful feature of the surveillance process. Intuition is defined as “understanding without rationale” (Benner & Tanner, p. 23).Expert nurses are able to recognize patterns and relate current clinical situations to past experience, integrate the knowledge of the patient’s disease with contextual knowledge about the patient, and are skilled in their specialty areas.Expert nurses also practice deliberative rationality-the capacity to view a clinical scenario from different perspectives; they also possess a sense of salience- the ability to identify the most pertinent observations in a complex assessment (Benner & Tanner). Therefore, expert nurses are able to immediately detect changes in a patient’s condition and intervene to prevent adverse occurrences (Christensen & Hewitt-Taylor, 2006; Houser, 2003).Years of experienceExperience is necessary for gaining expertise, but the two are not necessarily interchangeable (Christensen & Hewitt-Taylor, 2006; Houser, 2003). The number of years of experience, however, provides exposure to different patient conditions and clinical scenarios that contribute to the development of knowledge, technical skills, and critical thinking (Benner, 1984; Newman, 1990).Research that links experience to patient outcomes is scarce; however, existing findings are promising. For example, Tourangeau, Giovannetti, Tu, and Wood (2002) found that each additional year of nurse experience was associated with six fewer patient deaths for every 1000 patients discharged from urban community hospitals. In another study, units with more experienced nurses reported lower rates of medication errors and adverse events (Blegen, Vaughn, & Goode, 2001).Nurse practice environmentThe nurse practice environment is defined as “the organizational characteristics of a work setting that facilitate or constrain professional nursing practice” (Lake, 2002, p. 178). Several instruments have been developed to measure the nurse practice environment. One of these, the Practice Environment Scale of the Nursing Work Index (PES-NWI; Lake, 2002), is used to measure elements that are critical to nurse surveillance. Furthermore, the PES-NWI has been endorsed by the National Quality Forum (NQF) as a nursing-sensitive standard measure for inpatient care (NQF, 2004).The five domains of the PES-NWI are:Nurse Participation in Hospital Affairs;Nursing Foundations for Quality of Care;Nurse Manager Ability,Leadership and Support of Nurses;Staffing and Resource Adequacy; andCollegial Nurse-Physician Relations (Lake, 2002).Nurse participation in hospital affairs is not an obvious component of surveillance. However, in hospitals where nurses are able to influence administrative decisions and policies, nurses are likely to be more efficient in their practice (Aiken, Lake, Sochalski, & Sloane, 1997).Nursing foundations for quality care, such as patient assignments that promote continuity of care, are conducive to surveillance by enhancing the accumulation of knowledge about a patient.Job performance and productivity, including surveillance, depending on the support and ability of the nurse manager (Kramer, Schmalenberg, & Maguire, 2004).Nurses need the staffing support to have adequate time to spend with their patients to perform surveillance, as well as adequate resources available to them to implement necessary interventions (Laschinger & Lieter, 2006; McCusker, Dendukuri, Cardinal, Laplante, & Bambonye, 2004).Further, collegial relationships with physicians are essential to effective surveillance through the exchange of information vital to the patient’s clinical condition (Baggs et al., 1999; Kramer & Schmalenberg, 2004b).Nurse Surveillance and OutcomesBetter nurse surveillance is considered to be the link between better RN staffing/education and the prevention of mortality and failure-to-rescue in surgical patients (Aiken et al., 2003; Aiken, Clarke, Sloane, Sochalski, et al., 2002; Clarke & Aiken, 2003). With the elements of nurse surveillance capacity in place, nurses are better able to perform adequate surveillance of patients and initiate a timely response when a complication or adverse event is detected. Therefore, theoretically, multiple adverse outcomes may be used to assess the effectiveness of hospital nurse surveillance capacity, including mortality and failure-to-rescue. We posit that nurse surveillance capacity has the same relevance for all patient populations and non-mortality outcomes. Other outcomes of nurse surveillance capacity may include quality of care and adverse events, such as falls and nosocomial infections.MethodsData SourceThis study was a secondary analysis of data derived from a 50% random sample survey of Pennsylvania RNs that was conducted in 1999. The survey response rate was 52%, for a total of 43,329 RNs (Aiken et al., 2001). The survey was developed to examine the relationships between nurse staffing, work environment, and patient outcomes (Aiken, Clarke, & Sloane, 2002). The survey contained questions about hospital work environments, workload, workplace safety, quality of care assessments, demographics, education, and experience. Data reflecting individual patient characteristics were not collected in the survey.SampleOf the 43,329 respondents, 13,204 nurses indicated they worked in one of the 210 acute care hospitals in the state. Nurses were included in the final sample for this study if they identified their primary position as a staff nurse working in acute care (excluding the emergency room). Hospitals were included in the sample that had a sufficient number of respondents to assure reliable aggregate values of surveillance capacity variables, as described elsewhere (Aiken, Clarke, Sloane, Sochalski, et al., 2002). An average of 60 nurse respondents from each hospital completed questionnaires. One-half of the hospitals had more than 50 nurse respondents and over 80% of the hospitals had more than 25 nurse respondents. The final sample for this analysis consisted of 9,232 RNs in 174 hospitals in the state of Pennsylvania.MeasuresEmpirical referents were extracted from the Pennsylvania nurse survey to operationalize nurse surveillance capacity. A Hospital Nurse Surveillance Capacity Profile was constructed for each hospital by ranking hospitals on a set of RN characteristics (staffing, education, clinical expertise, and years of experience) and the nurse practice environment. An aggregate measure of hospital nurse surveillance capacity was constructed by calculating a hospital’s average ranking across indicators. Nurse-assessed quality of care and two adverse event variables (nosocomial infections and patient falls with injuries) were the outcomes in this study.StaffingNurses were asked to provide the number of patients cared for on their last shift. The mean number of patients cared for was calculated across all staff nurses within a hospital who reported caring for at least 1 but no more than 20 patients on their last shift. Aiken, Clarke, Sloane, Sochalski, and Silber (2002) considered this measure of staffing to be more accurate than administrative database sources. Harless and Mark (2006) discussed the bias introduced into staffing estimates when using administrative financial data to predict staffing allocation levels.EducationNurses were asked to provide their highest level of education in nursing. Respondents chose from diploma, associate degree, baccalaureate degree, master’s degree, or other. The education variable was operationalized as the proportion of staff nurse respondents within each hospital holding a baccalaureate degree or higher.Clinical expertiseNurses were asked to describe their clinical nursing expertise by choosing from one of the following response categories defined by Benner (1984): advanced beginner, competent, proficient, and expert. Responses were coded 1 to 4 respectively. The clinical expertise variable was calculated as the mean expertise of nurse respondents in each hospital.Years of experienceNurses were asked to provide the number of years they had worked as an RN. The experience variable was calculated at the hospital-level as the mean number of years of RN experience.Nurse practice environmentThe nurse practice environment was measured using the PES-NWI (Lake, 2002). The PES-NWI includes 31 items that use a 4-point Likert scale (strongly agree, somewhat agree, somewhat disagree, and strongly disagree) to assess nurses’ perceptions of the presence of organizational characteristics in their hospitals.A mean score for each of the five subscales was calculated at the hospital-level from the hospital mean of the individual items composing each subscale (Rousseau, 1985; Verran, Gerber, & Milton, 1995).The reliability of the five subscales was examined at the hospital-level by calculating the intraclass correlation coefficient (ICC (1, k)) across hospitals using a minimum criterion of .60 (Glick, 1985).All five subscales demonstrated acceptable reliability at the hospital-level with ICC (1, k)s ranging from a low of .67 for the Collegial Nurse-Physician Relations subscale to a high of .89 for the Participation in Hospital Affairs subscale. Internal consistency coefficients (Cronbach’s alphas) for the five subscales ranged from .78 to .85.Discriminate validity of the PES-NWI has been demonstrated by its ability to detect differences in the nurse practice environments of a magnet and non-magnet hospitals (Lake & Friese, 2006).Quality of careNurses were asked to rate the quality of nursing care delivered to patients on their unit using a 4-point Likert scale of excellent, good, fair, and poor. The reliability of the quality of care variable was examined at the aggregate level by calculating the ICC (1, k) across hospitals. The ICC (1, k) for quality of care was .73. Responses were collapsed into categories of poor/fair and good/excellent care to examine associations with the nurse surveillance capacity rankings.Adverse eventsNurses were asked to report how often two different adverse events, nosocomial infections, and patient falls with injuries, occurred involving their patients over the past year.The frequency of adverse events was measured using a 4-point Likert-type scale of never, rarely, occasionally, or frequently. The reliability of the adverse event measures at the aggregate level was examined by calculating the ICC (1, k) across hospitals. The ICC (1, k)s for nosocomial infections and patient falls with injuries were .73 and .71, respectively. Responses were collapsed into categories of never/rarely and occasionally/frequently to examine associations with the nurse surveillance capacity rankings.Data AnalysisThe purposes of the data analysis were to describe hospitals’ nurse surveillance capacity, to rank hospitals by nurse surveillance capacity, and to associate hospitals’ average ranking with quality of care indicators. Individual nurse responses were examined to assess demographics. Nurse responses were then aggregated to the hospital-level to create the nurse surveillance capacity indicators.Distributions for the aggregated variables were calculated. To create a Hospital Nurse Surveillance Capacity Profile, the hospitals first were ranked on each nurse surveillance capacity indicator so that they rank on each indicator reflected the hospital’s placement among all hospitals.A profile was developed to display hospital ranks by deciles for clarity of comparison, with 1 as the lowest and 10 as the highest decile. A Hospital Nurse Surveillance Capacity Profile was created for each of the 174 represented hospitals.Hospitals’ overall nurse surveillance capacity was then calculated as the mean ranking across all nine nurse surveillance capacity indicators. Finally, hospitals’ overall nurse surveillance capacities were ordered into deciles, with 1 as the lowest and 10 as the highest decile. One hospital profile from the overall highest decile and another from the lowest were selected to illustrate and to contrast a highly ranked hospital and its consistent performance across indicators with a low ranked hospital.To associate hospitals’ rankings with quality of care indicators, outcomes of hospitals in the highest and lowest deciles of overall nurse surveillance capacity ranking were compared. Nurse responses were aggregated to the hospital-level to create the outcome measures. Same-source bias was of concern as the nurse survey was used to measure the independent and dependent variables. Therefore, a split sample approach was used to test the robustness of the estimates. In every hospital, a random half of the nurses’ responses was aggregated for the organizational measures. The other half was aggregated for the outcome measures, and the analysis was repeated.FindingsNurse Respondent DemographicsDemographics of the nurse respondents were examined. Nearly all respondents were female (94%). The average respondent was 39 years of age. The majority of the nurses worked on a medical/surgical unit (38%); about a quarter of the respondents (24%) worked in intensive care.Nurse Surveillance Capacity DistributionsDistributions for the nurse surveillance capacity variables for the 174 study hospitals are shown. Average staffing across all hospitals was just over 5 patients per nurse. On average, one-third of the nurses within a hospital held at least a baccalaureate degree had over 13 years of experience as an RN and rated themselves as competent to proficient in their clinical expertise.A low proportion of hospitals (1 in10) had a majority of nurses who rated their practice as proficient or expert (average expertise ≥3.0).Hospitals tended to score highest on the Nursing Foundations for Quality of Care subscale of the PES-NWI; the lowest scored subscale was Staffing and Resource Adequacy.Nurse Surveillance Capacity RankingsNine percent of hospitals ranked above the 50th percentile on all nurse surveillance capacity indicators. Nurses in the highest-ranked hospitals took care of approximately two fewer patients than nurses in the lowest decile of nurse surveillance capacity.Over 40% of the nurses in the highest-ranked hospitals had a bachelor’s degree as compared to 20% of nurses in the lowest decile. Nurses in the highest decile of nurse surveillance capacity also rated their clinical expertise higher than those in the lowest grouping.Hospitals in the top decile of nurse surveillance capacity also had more years of RN experience as compared to the bottom decile. Nurses in hospitals in the top decile of nurse surveillance capacity consistently evaluated the nurse practice environment more favorably as compared to nurses in the lowest decile. The differences in means across all five subscales of the PES-NWI were sizable. The largest difference between deciles was observed in the Staffing and Resource Adequacy subscale.Figure 1 illustrates the Hospital Nurse Surveillance Capacity Profile of two hospitals chosen from the highest and lowest deciles after average ranking across indicators. The figure compares the Hospital Nurse Surveillance Capacity Profile of a hospital with consistently high rankings, theoretically demonstrating a strong capacity for nurse surveillance, with a hospital in which the capacity for surveillance may be deficient based on the proposed conceptualization. Hospital values for each of the nine indicators are displayed to provide a more meaningful comparison.The nurse surveillance capacity of hospitals was examined in this study. Nurse surveillance capacity was operationalized as a set of organizational features derived from RN characteristics and reports of the nurse practice environment collectively referred to as the Hospital Nurse Surveillance Capacity Profile.The results of this study suggest that an organization composed of well educated, expert, and experienced nurses, with adequate staffing and a supportive practice environment, promotes quality of care and prevention of two adverse events—falls with injury and nosocomial infections. The hypothesized mechanism for this association is more effective surveillance across individual nurses and overtime.The findings from this study suggest that modifying organizational features to support surveillance is a promising strategy for reducing adverse patient outcomes and improving the quality of care.The analysis confirmed that the organizational characteristics that foster nurse surveillance are associated with a better quality of care and fewer falls with injury and nosocomial infections based on self-reports from nurses. Hospitals in the highest and lowest deciles of overall nurse surveillance capacity indicators were compared relative to the quality of care and adverse events.Nurses in the highest-ranked hospitals of nurse surveillance capacity reported better quality of care and less frequent nosocomial infections and patient falls with injuries.We operationalized nurse surveillance capacity in a way that the concept could be measured. Multiple literature syntheses have demonstrated the association between nurse staffing and patient outcomes, including mortality, complications, and length of stay (Kane et al., 2007; Lang, Hodge, & Olsen, 2004; Lankshear, Sheldon, & Maynard, 2005). In a comprehensive review of the literature, Kazanjian, Green, Wong, and Reid (2005) concluded that the hospital nursing environment affects patient outcomes; however, the need for additional research was highlighted. The IOM report, Keeping Patients Safe: Transforming the Work Environment of Nurses (Page, 2004), cited all of the identified nurse surveillance capacity indicators as important factors to consider in the examination of patient care and safety.Management Applications of the ProfileIn this study, we translated the theoretical underpinnings of and organizational contributors to nurse surveillance that has been established in the literature into a measure of nurse surveillance capacity and organizational property that can be monitored and modified by nurse executives and hospital administrators.With this approach, administrators could profile their hospital’s surveillance capacity, benchmark that profile against peer hospitals with similar characteristics, and evaluate themselves over time. Benchmarking against similar hospitals with comparable macro characteristics, such as location, size, and teaching status, carries an additional advantage, as patient characteristics could be accounted for by proxy of hospital characteristics.Further, the NQF’s (2004) endorsement of the PES-NWI and the technical specifications prepared by The Joint Commission (JCAHO, 2005) allows hospitals to benchmark their institution against a broader range of hospitals. The Hospital Nurse Surveillance Capacity Profile can be used to detect weaknesses in the nurse surveillance system and highlight areas in which more attention and resource allocation are needed to ensure patient safety and quality care.The findings in this study demonstrate how the organizational capacity for nurse surveillance may be measured and evaluated. Institutions increasingly have the data to construct their own Hospital Nurse Surveillance Capacity Profiles.The Hospital Nurse Surveillance Capacity Profile could be added to a dashboard monitored by nurse executives and hospital administrators. Using the Hospital Nurse Surveillance Capacity Profile for benchmarking across like hospitals may only be possible through national databases, like the National Database of Nursing Quality Indicators (NDNQI), or health care systems that have multiple facilities, where data can be collected from and aggregated for a large number of facilities. For other facilities, the concept may be feasible for internal quality improvement at the nursing unit level. In addition to comparing similar units within hospitals, individual specialty units may follow their own surveillance capacity over time.Research ConsiderationsThis study is a secondary analysis of survey data. The use of survey data to describe organizations is challenged by the issues of respondent bias, response rate, and aggregation. The strengths of this survey data included a large number of respondents and hospitals and a research design that did not permit hospitals to opt-out.A limitation was deriving the data from nurses working in a single large state. The response rate of 52% is considered good by the current standards of social survey research (Asch, Jedrziewski, & Christakis, 1997). Individual respondents were similar to the Pennsylvania nurses in the National Sample Survey of Registered Nurses (Aiken, Clarke, Sloane, Sochalski, et al., 2002; U.S. Department of Health and Human Services, 2000). The survey data were compared previously with American Hospital Association (AHA) annual survey data and the findings revealed that the number of responding nurses from each hospital was directly proportional to the number of RNs in each hospital as reported by AHA (Aiken et al., 2003).The amount of same-source bias was likely to be reduced by the aggregation of our independent and dependent variables to the hospital-level (Rousseau, 1985; Verran et al., 1995). The effect sizes were equivalent in the split sample approach; therefore, the amount of same-source bias was negligible. Nurse informants responding to Likert-type scale items provided the outcomes in this study. The three outcome measures demonstrated reliable estimates using standard criteria. Recall bias is also a threat to the accuracy of these reports. However, nurses’ retrospective reports of adverse events have been substantiated by adverse event data collected prospectively (Aiken, Sloane, & Klocinski, 1997; Gerolamo, 2006).Although these data were collected in 1999, the concepts discussed in this study remain salient to current hospital executives (Donaldson, Brown, Aydin, Bolton, & Rutledge, 2005). Several study measures have been disseminated widely since 1999 through endorsement by the NQF (2004), the development of technical specifications byThe JCAHO (2005), and by inclusion in the annual RN Survey of the American Nurses Association-sponsored NDNQI, which was conducted in over 500 hospitals in 2007 (NDNQI, 2006; 2008).Future ResearchMethods to directly measure nurse surveillance present a challenge to the field. Nursing intervention classification systems’ measurement of nurse surveillance has been useful to begin to understand the process. However, these systems lack the specificity needed to construct a measure that accounts for each component of the surveillance process, and the organizational context in which nurses perform surveillance.To ensure the generalizability of these findings an important next research step would be to replicate and improve upon the current study using new data sets. Research on nurse surveillance capacity could expand to incorporate and evaluate patient characteristics and outcomes. By contrast to nurse reports, objective patient outcome data, including mortality, require patient-level risk-adjustment. To date, well-developed risk adjustment models exit only for surgical patient mortality using solely administrative data. Although efforts to risk-adjust mortality for medical and other patient populations have been made (Escobar, Greene, Scheirer, Gardner, Draper, et al., 2008; Tourangeau & Tu, 2003), these models need further development and refinement.Nurse surveillance capacity may be associated with other hospital structural characteristics, such as size, teaching status, and location. Opportunities to enhance nurse surveillance capacity, however, may be limited by hospital resource constraints.Additional research may reveal how units might be staffed to offset surveillance capacity inadequacies, such as insufficient RN staffing, few nurses with baccalaureate degrees, lower expertise, many new graduates, or unfavorable environments.We plan to examine this question in future work. The influence of physician workforce characteristics and technology status on the quality of surveillance will be important to consider. Moreover, information technology is a developing area, and its effectiveness on nurse surveillance remains unclear (Koppel et al., 2005).

1968 Diagnostic and Statistical Manual (DSM-II), Multiple Personality Disorder was called hysterical neurosis, dissociative type and was defined as an alteration to consciousness and identity.In 1980, the DSM-III was published and the term "dissociative" was first introduced as a class of disorders.Separating Fact from Fiction: An Empirical Examination of Six Myths ...https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959824/Published 2013, Dissociative identity disorder (DID) is defined in the fifth edition of the DSM ... The first published cases are those of Jeanne Fery, reported in 1586, .... in which DID or multiple personality disorder (MPD) had been diagnosed.Understanding Multiple Personality Disordershttps://www.nurseslearning.com/courses/nrp/NRP-1618/Section1/index.htm“Introduction. Since the first exploration of the phenomenon of Multiple Personality Disorder some hundred years ago, the diagnosis has been the recipient of much confusion and skepticism. Because its presentation can be so dramatic and the precipitating trauma so humanly unacceptable, it was passed off as the hysterical behavior of overwrought or spoiled women. However, with the attention in recent years to the issue of child abuse, Multiple Personality Disorder has gained acceptance as a valid psychiatric diagnosis. Once considered rare, the reported incidence has increased steadily since 1980. It occurs in 1.2% of the general psychiatric population (Steele, 1989 (making it about as common as schizophrenia).Dissociative Disorders (DD), specifically Multiple Personality Disorder (MPD), have received much attention in the past decade, though they are not new phenomena. In fact, these disorders were among the first psychiatric conditions to be scientifically investigated by the nineteenth-century pioneers of psychiatric medicine (Putnam, 1991). However, in the twentieth century, the work of such pioneers was largely set aside and forgotten as Freud introduced his psychoanalytic model which substituted the idea of repression for dissociation in dynamic formulations.MPD remains highly controversial among psychiatric professionals. The reality of the disorder is often challenged. Putnam feels “this distorts the scientific process and places an extra burden of proof on MPD that is not demanded of other psychiatric disorders.” MPD and DD have met all the requirements expected of other psychiatric diagnoses, and Putnam maintains that “by this standard, MPD and the dissociative disorders are as “real” as any other psychiatric condition.”Based on my research and having assisted many people with psychogenic amnesia and Dissociative Idenity I know these coping strategies are caused by profound, severe and relentless mental/emotional, physical and/or sexual abuse. The following sources might be of interest.1. 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A tulpa is an alter-self created in the mind, acting independently of, and parallel to your core consciousness. The alter-self is able to think, and have their own free will, emotions, and memories. In short, a tulpa is like a sentient person living in your head, separate from your core self. A tulpa is created for self-preservation during an extended period of horrific mental/emotional, physical, and/or sexual abuse.While tulpamancy skills are a good coping mechanism the amount of time your core self is excluded in day-to-day interactions is fundamentally the same. In fact, in some instances, one of the alter-self proclaims it has the right to become an alternate core self.Each alter-self needs to discover what experiences and trauma each hold and process the experience and trauma to the degree the alter-self can integrate into the core-self.When someone begins a holistic transformation/transmuting process, no matter how dire their predicament seems to be, I KNOW if she/he is WILLING to do the mental/ emotional discovery work; releasing and transforming beliefs, thoughts and feelings, anything can be transformed/transmuted. The word ‘incurable’ or ‘impossible’ only means that the particular condition, symptom or diagnosis cannot be ‘cured’ by ‘outer’ methods and that she/he needs to GO WITHIN to effect the transformation/transmuting. The condition, symptom or diagnosis came from mental/emotional distress and will go back to nothing.When beliefs, thoughts, feelings, and behavior are accessed and addressed at the unconscious, subconscious and cellular level, the 'cause' of any and all symptoms and behavior become crystal clear--it is mental/emotional, physical, and spiritual trauma/distress manifesting in the behavior and symptoms you experience.A Transformation/Transmuting process is a clear, concise, and direct method of transforming/transmuting the mental, emotional and physical symptoms that transcends traditional protocols while retaining a professional focus. Deep Healing avoids prescription and OTC drugs, body parts removed, artificial hypnotic inductions, and psychic interventions. The process ties in directly with the experiences and needs of the person. The process is down-to-earth, to-the-point, practical, fearless and with 20+ years experience and centuries of holistic health care protocol success I know there is no doubt Deep Healing is effective.1968 Diagnostic and Statistical Manual (DSM-II), Multiple Personality Disorder was called hysterical neurosis, dissociative type, and was defined as an alteration to consciousness and identity.In 1980, the DSM-III was published, and the term "dissociative" was first introduced as a class of disorders.Separating Fact from Fiction: An Empirical Examination of Six Myths ...Separating Fact from Fiction: An Empirical Examination of Six Myths About Dissociative Identity DisorderPublished 2013, Dissociative identity disorder (DID) is defined in the fifth edition of the DSM ... The first published cases are those of Jeanne Fery, reported in 1586, .... in which DID or multiple personality disorder (MPD) had been diagnosed.Understanding Multiple Personality DisordersUnderstanding Multiple Personality Disorders“Introduction. Since the first exploration of the phenomenon of Multiple Personality Disorder some hundred years ago, the diagnosis has been the recipient of much confusion and skepticism. Because its presentation can be so dramatic and the precipitating trauma so humanly unacceptable, it was passed off as the hysterical behavior of overwrought or spoiled women. However, with the attention in recent years to the issue of child abuse, Multiple Personality Disorder has gained acceptance as a valid psychiatric diagnosis. Once considered rare, the reported incidence has increased steadily since 1980. It occurs in 1.2% of the general psychiatric population (Steele, 1989 (making it about as common as schizophrenia).Dissociative Identity Disorders (DID), specifically Multiple Personality Disorder (MPD), have received much attention in the past decade, though they are not new phenomena. In fact, these disorders were among the first psychiatric conditions to be scientifically investigated by the nineteenth-century pioneers of psychiatric medicine (Putnam, 1991). However, in the twentieth century, the work of such pioneers was largely set aside and forgotten as Freud introduced his psychoanalytic model which substituted the idea of repression for dissociation in dynamic formulations.MPD remains highly controversial among psychiatric professionals. The reality of the disorder is often challenged. Putnam feels “this distorts the scientific process and places an extra burden of proof on MPD that is not demanded of other psychiatric disorders.” MPD and DD have met all the requirements expected of other psychiatric diagnoses, and Putnam maintains that “by this standard, MPD and the dissociative disorders are as “real” as any other psychiatric condition.”Based on my research and having assisted many people with psychogenic amnesia and Dissociative Identity Disorder I know these coping strategies are caused by profound, severe, and relentless mental/emotional, physical, and/or sexual abuse. The following sources might be of interest.1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed Arlington, VA: APA, 2013. [Google Scholar]2. Putnam FW. Dissociation in children and adolescents: a developmental perspective. New York: Guilford, 1997. [Google Scholar]3. Simeon D, Loewenstein RJ. Dissociative disorders. 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