As Chair of the Ph.D. (Health Services) Dissertation Committee for Ellem Rice, Ph.D., I am pleased to post the ABSTRACT of her Dissertation(February 2011). Questions and comments should be directed to Dr. Rice ellenbentz@msn.com
ABSTRACT
"Transitioning from Practical to Registered Nurse: A Phenomenological Inquiry of Graduates of a Competency Based Nursing Program"
The United States is experiencing a nursing shortage, the result of social, financial, and technological supply and demand factors. This research explored the intersection of nontraditional nursing education, modern nursing practice, and the current nursing shortage through a general system perspective. The study used a qualitative, retrospective, interview design to gain an understanding of the transition experiences of graduates of a nontraditional, competency based program for licensed practical nurses. Research questions focused on role development in the first year of nursing practice. Interview transcripts were analyzed using Van Maanen’s technique for vocational role development analysis. Benner’s theory of nursing development was used to contrast the experiences of the nontraditional graduates with previously published transition research in traditional graduates. Analysis indicated that the nontraditional graduates began nursing practice at an advanced level but expressed limited experience with expert nursing concepts. Results have the potential to contribute to a paradigm shift in nursing clinical education and intentional nursing role development. The implementation of cost-efficient and effective nursing curriculum positively impacts health care by improving patient safety and workplace morale, and by promoting critical thinking and nursing autonomy. Fostering ongoing role development for nurses contributes to a competent workforce and quality outcomes. Evidenced based improvements in nursing education promise social change through reallocation of financial and human resources to the broader social objectives of ensuring quality nursing care, creating networks of care, expanding access to health services, and promoting and supporting population health initiatives.
Saturday, February 12, 2011
Wednesday, January 26, 2011
Learning Culture and Other Factors Affecting the Adoption of Electronic Medical Records in a Tertiary-Care Teaching Hospital
I was pleased to serve as a Member of the Ph.D. Doctoral Committee for Dr. Virgina Chavez. I encourage all of my doctoral students to consider publication of their rssearch results in a peer-reviewed, scholarly journal. Her timely research relating to electronic medical records was published in a recent on-line edition of the AAMA EXECUTIVE (American Academy of Medical Administrators).
Robert E. Hoye, Ph.D. FAAMA, FRSH
AAMA State Director for Kentucky
Learning Culture and Other Factors Affecting the Adoption of Electronic Medical Records in a Tertiary-Care Teaching Hospital
Virginia D Chavis, PhD
Senior Project Analyst
Intel Corporation
Chandler, AZ
Florence-Betty C. Roque, RN, BSN, MSN, ND, CPNP
Primary Care Provider
Rio Grande Medical Group
Deming, NM
Katherine Kenny, DNP, RN, ANP-BC, CCRN
Clinical Associate Professor
Arizona State University
Phoenix, AZ
Background
One of the highest priorities in healthcare reform is to change a paper-based culture to one that relies on electronic record keeping. The shift from paper to electronic files offers a different way for health professionals to think about patient needs. Improvements in the exchange of medical information may lead to better patient care and innovative ways to treat diseases and disorders. Using electronic medical records (EMR) in hospitals, medical centers, and private practices requires system implementation managers to diagnose the level of workers’ resistance to technology and then decide how best to motivate them to use it.
Medical record reform research (Margalit et al., 2006; Menachemi et al., 2007; Menachemi, Hikmet, Stutzman, & Brooks, 2006; Nowinski, Becker, Reynolds, Beaumont, Caprini, Hahn, et al., 2007) captures the impact technology acceptance has on various organizational factors. Accounting for these factors, many EMR implementations continue to fail. A leading cause is the information technology-centric approach, one that overlooks how health information technology (HIT) will affect the organization’s structures and processes (Berg, 2001). Other challenges, such as identifying professionals who will embrace the new technology and identifying the system features that become objects of resistance, also contribute to failure. To reduce the risk of product implementation failure, EMR should “be conceived as organizational development” (p. 147) and not a “mere” technical project (p. 148). An organizational development (OD) approach puts the emphasis on core business processes rather than the technology functions. Information and technology usage and barriers to adoption are vital elements addressed in an OD approach. The approach also can help manage organizational learning culture changes and IT capabilities.
Limited literature exists that examines the role of learning mechanisms. In the past five years, the amount of literature that keeps abreast of EMR implementation factors increased (Anderson, 2007; Anderson & Balas, 2006; Baker, Persell, Thompson, Soman, Burgner, Liss, et al., 2007; Croll & Croll, 2007; Christensen & Grimsmo, 2005; Feldstein et al., 2006; Lapointe & Rivard, 2006). Analysis of the literature showed that little formal data were available to understand the impact technology has on organizational learning. It is therefore difficult to understand if an organizational learning model is an adequate approach in healthcare settings. The literature review also showed that most EMR implementations are managed as information technology (IT) projects rather than using relevant and reliable organizational development strategies. The empirical insight also identifies common barriers to HIT adoption and describes common attitudes towards a healthcare learning environment. Unfortunately, innovation deployment often includes implementation strategies not congruent with the complex professional roles and relationships in medical environments. Moreover, a limited number of studies have significantly examined technology adoption among physicians, nurses and other medical specialists who care for patients in a multi-disciplinary medical setting.
Given the gaps in literature, the purpose of this IRB-approved quantitative survey research was to identify and understand technology adoption barriers by examining technology-usage behavior (e.g., use of EMR), technology adoption factors, and employees’ attitudes towards organizational learning. It also aimed to assess if a significant relationship exists between technology adoption and target variables, such as age, tenure with the organization, and overall level of education. We examined the relationship between technology adoption and principles of learning organization by investigating medical professionals’ perceptions of the learning culture of the research site and other barriers to EMR adoption. We were interested in knowing if a correlation difference existed between technology adoption scores for a learning mechanism and the learning organization scores, if a significant difference existed in the technology adoption scores for medical professionals who have prior EMR experience compared to those with no experience, and if a correlation difference existed in demographic characteristics of medical professionals and technology adoption scores. Data on the barriers to EMR use among medical staff was used to examine these correlations. Lastly, We presented data on learning organization score, which may serve as a benchmark for understanding which learning dimensions and human factors best influence the widespread adoption of an EMR.
Methods
Survey Sample
We selected all employed medical professionals at SJHMC Hospital and Medical Center (SJHMC), in Phoenix, Arizona. Medical professionals were defined as registered nurses (RNs), physician (including employed residents), and other medical professionals such as pharmacists and physical therapists. Using Sample Size Calculator by Creative Research Systems®, sample size and power calculations were determined. Based upon a medical population size of N = 1576, a confidence interval of 5% and a confidence level of 95%, the minimal sample size needed was 309. We are confident that all members of the population would have answered that learning environment influenced technology adoption.
Survey Design and Administration
Surveys were completely anonymous. It was publicized in the hospital’s newsletter and nursing huddles. The study was conducted during two periods: October 2009 – November 2009 and 2 weeks in January 2010. For the first collection, a survey along with a cover letter was distributed to 376 faculty physicians and residents, as well as 1,200 nurses, including mid-level practitioners. Paper versions of the survey were handed out to nurses and residents, and electronic surveys were emailed to faculty physicians. All participants, regardless of distribution method, had the option to either return the completed survey in interoffice mail or complete the survey online. Nonmedical staff such as janitors, volunteers, and operational staff (e.g., human resources, legal, and information technology), contingent medical staff, and administrative medical staff were excluded.
A follow-up announcement reminding staff of the study was sent two weeks after the initial invitation. We tracked respondents by hospital units. For the second period, nonrespondents were identified using the unit categories. These groups were handed a second survey package, which included the cover letter, survey, and return envelope.
The technology and Learning Organization Questionnaire was a two-part, self-administered questionnaire. Usage permissions were obtained prior to data collection. The first part, the technology assessment, captured general information technology use, EMR use, and barriers to EMR use. The instrument was developed by Menachemi et al. (2006) and was adopted with some minor modifications. For example, the word “practice” was changed to “center or clinic.” The second portion of the questionnaire came from the Dimensions of the Learning Organization Questionnaire® (DLOQ-A) developed by Yang (2003). It is a validated questionnaire composed of seven discipline areas that measure “changes in organizational learning practices and culture as perceived by the employees” (Marsick & Watkins, 2003, as cited in Dymock & McCarthy 2006, p. 528). The organization adoption score was correlated to organizational learning scores and other variables.
Participants completing the questionnaire online were required to give consent. Once the consent was electronically acknowledged, the participant gained access to the questions. Participants that completed the paper version returned the questionnaire through interoffice mail in a preaddressed envelope. All mailed responses were entered into the electronic database, and data was verified and cross-checked by an independent statistician. In addition, SJHMC Hospital and Medical Center Institutional Review Board (IRB approval number - 08BN042) and Walden University (IRB approval number - 09-29-09-0287953) evaluated and approved this study.
Statistical Methods
Analyses included standard descriptive and inferential statistics. Descriptive statistics was used to describe respondents’ characteristics such as age range, gender, years of experience as a nurse or physician, and years of employment at SJHMC. Learning and technology adoption and significances were determined through t test analysis. Inferential statistical correlation analysis was performed to validate whether a correlation or association existed between two the types of scores); two-sample t tests compared the means of the two populations, and ANOVA. JMP® software was used for analysis, and significance was considered at the p < 0.05 level. With survey research, response bias is a possibility. According to Menachemi (2006), surveys are a valuable method for gathering information for a geographically diverse population, especially when face-to-face interviews are not possible because of cost and/or time constraints. Surveys of physicians also typically yield lower response rates than other healthcare professionals. To attempt to correct for nonrespondent bias physician respondents were compared to nurse respondents, and the return rates were the same. The response rate for nurses was 17.4% and for physicians it was 17.3%. From these numbers, the percentage of nurses that responded equaled the percentage of physicians that responded. Surveys were distributed to all clinical units; however, demographic profiles of the clinical units are not known. Therefore, it is not possible to correct for nonrespondent bias within the two groups. The study conducted by Menachemi and Brooks (2006), which used the same technology assessment survey, compared responders and nonresponders with respect to known demographics and found “no significant evidence of bias was detected even after employing common techniques used to identify response bias” (p. 85). Results Demographics Study participants included registered nurses (RNs), physician (including employed residents), and other medical professionals such as pharmacists and physical therapists. Of the 337 surveys returned (a 21.4% participation rate), 7 respondents were excluded, 69 respondents (20.9%) reported themselves as physicians, and 220 (66.7%) reported their position as nurse. The final return rate was 21%. The percentage of physicians that responded was equal to the percentage of nurses that responded. Demographic characteristics of the respondents are shown in Table 1. One nonemployed physician completed the survey, and those responses were removed from analysis. In addition, six administrative support staff members that would not use an EMR were excluded. Missing demographic answers were noted on the specific questions and the total respondents revised for that question. Respondents that did not answer or partially answered questions 10 and 17 were excluded from data analysis. The number of respondents for this analysis was adjusted to reflect missing responses. Table 1 Participants’ Demographic Characteristics Category Physicians Nurses Other or unknown Age range: < 35 36 (12%) 79 (26.3%) 2 (0.7%) 35-50 22 (7.3%) 91 (30.3%) 11 (3.7%) > 50 10 (3.3%) 46 (15.3%) 3 (1.0%)
Gender:
Male 35 (11.7%) 26 (8.7%)
Female 33 (11.0%) 189 (63.2%) 16 (5.4%)
Mean yrs. At SJHMC 4.6 (<1 – 33) 8.7 (<1 - 39) 8.3 (<1 - 26)
Mean yrs. since graduation 10.3 (<1 – 48) 12.8 (<1 - 41) 13.2 (<1 - 27)
Descriptive analysis of the demographic data consisted of frequencies and percentages of each variable. The majority of the participants were female (63.2%). More people reported their age range as between 35 and 50 (30.3%).
Barriers to the Use of EMRs
To compare barriers among SJHMC employed medical respondents, chi-square analysis was used, and significance was considered at the p < 0.05 level. Differences existed among physicians, nurses, and other medical staff (see Table 2). For example, no time to learn how to use such a system barrier was dramatically higher for nurses (53.8%) than physicians (34.7%) and other medical staff (18.2%). Another notable differences between nurses and the other groups were system difficulty (50.6% vs. 30% for physicians and 9.1% for other medical staff). Patient confidentiality ranked at 40% for both non-nurse groups, but nurses ranked it at 62.1%. The rank for patient resistance was 43.8% and was considerably lower by physicians (14%) and other medical staff (11.1%). Nurses, more frequently than the other two medical groups, indicated more barriers to using EMR.
Robert E. Hoye, Ph.D. FAAMA, FRSH
AAMA State Director for Kentucky
Learning Culture and Other Factors Affecting the Adoption of Electronic Medical Records in a Tertiary-Care Teaching Hospital
Virginia D Chavis, PhD
Senior Project Analyst
Intel Corporation
Chandler, AZ
Florence-Betty C. Roque, RN, BSN, MSN, ND, CPNP
Primary Care Provider
Rio Grande Medical Group
Deming, NM
Katherine Kenny, DNP, RN, ANP-BC, CCRN
Clinical Associate Professor
Arizona State University
Phoenix, AZ
Background
One of the highest priorities in healthcare reform is to change a paper-based culture to one that relies on electronic record keeping. The shift from paper to electronic files offers a different way for health professionals to think about patient needs. Improvements in the exchange of medical information may lead to better patient care and innovative ways to treat diseases and disorders. Using electronic medical records (EMR) in hospitals, medical centers, and private practices requires system implementation managers to diagnose the level of workers’ resistance to technology and then decide how best to motivate them to use it.
Medical record reform research (Margalit et al., 2006; Menachemi et al., 2007; Menachemi, Hikmet, Stutzman, & Brooks, 2006; Nowinski, Becker, Reynolds, Beaumont, Caprini, Hahn, et al., 2007) captures the impact technology acceptance has on various organizational factors. Accounting for these factors, many EMR implementations continue to fail. A leading cause is the information technology-centric approach, one that overlooks how health information technology (HIT) will affect the organization’s structures and processes (Berg, 2001). Other challenges, such as identifying professionals who will embrace the new technology and identifying the system features that become objects of resistance, also contribute to failure. To reduce the risk of product implementation failure, EMR should “be conceived as organizational development” (p. 147) and not a “mere” technical project (p. 148). An organizational development (OD) approach puts the emphasis on core business processes rather than the technology functions. Information and technology usage and barriers to adoption are vital elements addressed in an OD approach. The approach also can help manage organizational learning culture changes and IT capabilities.
Limited literature exists that examines the role of learning mechanisms. In the past five years, the amount of literature that keeps abreast of EMR implementation factors increased (Anderson, 2007; Anderson & Balas, 2006; Baker, Persell, Thompson, Soman, Burgner, Liss, et al., 2007; Croll & Croll, 2007; Christensen & Grimsmo, 2005; Feldstein et al., 2006; Lapointe & Rivard, 2006). Analysis of the literature showed that little formal data were available to understand the impact technology has on organizational learning. It is therefore difficult to understand if an organizational learning model is an adequate approach in healthcare settings. The literature review also showed that most EMR implementations are managed as information technology (IT) projects rather than using relevant and reliable organizational development strategies. The empirical insight also identifies common barriers to HIT adoption and describes common attitudes towards a healthcare learning environment. Unfortunately, innovation deployment often includes implementation strategies not congruent with the complex professional roles and relationships in medical environments. Moreover, a limited number of studies have significantly examined technology adoption among physicians, nurses and other medical specialists who care for patients in a multi-disciplinary medical setting.
Given the gaps in literature, the purpose of this IRB-approved quantitative survey research was to identify and understand technology adoption barriers by examining technology-usage behavior (e.g., use of EMR), technology adoption factors, and employees’ attitudes towards organizational learning. It also aimed to assess if a significant relationship exists between technology adoption and target variables, such as age, tenure with the organization, and overall level of education. We examined the relationship between technology adoption and principles of learning organization by investigating medical professionals’ perceptions of the learning culture of the research site and other barriers to EMR adoption. We were interested in knowing if a correlation difference existed between technology adoption scores for a learning mechanism and the learning organization scores, if a significant difference existed in the technology adoption scores for medical professionals who have prior EMR experience compared to those with no experience, and if a correlation difference existed in demographic characteristics of medical professionals and technology adoption scores. Data on the barriers to EMR use among medical staff was used to examine these correlations. Lastly, We presented data on learning organization score, which may serve as a benchmark for understanding which learning dimensions and human factors best influence the widespread adoption of an EMR.
Methods
Survey Sample
We selected all employed medical professionals at SJHMC Hospital and Medical Center (SJHMC), in Phoenix, Arizona. Medical professionals were defined as registered nurses (RNs), physician (including employed residents), and other medical professionals such as pharmacists and physical therapists. Using Sample Size Calculator by Creative Research Systems®, sample size and power calculations were determined. Based upon a medical population size of N = 1576, a confidence interval of 5% and a confidence level of 95%, the minimal sample size needed was 309. We are confident that all members of the population would have answered that learning environment influenced technology adoption.
Survey Design and Administration
Surveys were completely anonymous. It was publicized in the hospital’s newsletter and nursing huddles. The study was conducted during two periods: October 2009 – November 2009 and 2 weeks in January 2010. For the first collection, a survey along with a cover letter was distributed to 376 faculty physicians and residents, as well as 1,200 nurses, including mid-level practitioners. Paper versions of the survey were handed out to nurses and residents, and electronic surveys were emailed to faculty physicians. All participants, regardless of distribution method, had the option to either return the completed survey in interoffice mail or complete the survey online. Nonmedical staff such as janitors, volunteers, and operational staff (e.g., human resources, legal, and information technology), contingent medical staff, and administrative medical staff were excluded.
A follow-up announcement reminding staff of the study was sent two weeks after the initial invitation. We tracked respondents by hospital units. For the second period, nonrespondents were identified using the unit categories. These groups were handed a second survey package, which included the cover letter, survey, and return envelope.
The technology and Learning Organization Questionnaire was a two-part, self-administered questionnaire. Usage permissions were obtained prior to data collection. The first part, the technology assessment, captured general information technology use, EMR use, and barriers to EMR use. The instrument was developed by Menachemi et al. (2006) and was adopted with some minor modifications. For example, the word “practice” was changed to “center or clinic.” The second portion of the questionnaire came from the Dimensions of the Learning Organization Questionnaire® (DLOQ-A) developed by Yang (2003). It is a validated questionnaire composed of seven discipline areas that measure “changes in organizational learning practices and culture as perceived by the employees” (Marsick & Watkins, 2003, as cited in Dymock & McCarthy 2006, p. 528). The organization adoption score was correlated to organizational learning scores and other variables.
Participants completing the questionnaire online were required to give consent. Once the consent was electronically acknowledged, the participant gained access to the questions. Participants that completed the paper version returned the questionnaire through interoffice mail in a preaddressed envelope. All mailed responses were entered into the electronic database, and data was verified and cross-checked by an independent statistician. In addition, SJHMC Hospital and Medical Center Institutional Review Board (IRB approval number - 08BN042) and Walden University (IRB approval number - 09-29-09-0287953) evaluated and approved this study.
Statistical Methods
Analyses included standard descriptive and inferential statistics. Descriptive statistics was used to describe respondents’ characteristics such as age range, gender, years of experience as a nurse or physician, and years of employment at SJHMC. Learning and technology adoption and significances were determined through t test analysis. Inferential statistical correlation analysis was performed to validate whether a correlation or association existed between two the types of scores); two-sample t tests compared the means of the two populations, and ANOVA. JMP® software was used for analysis, and significance was considered at the p < 0.05 level. With survey research, response bias is a possibility. According to Menachemi (2006), surveys are a valuable method for gathering information for a geographically diverse population, especially when face-to-face interviews are not possible because of cost and/or time constraints. Surveys of physicians also typically yield lower response rates than other healthcare professionals. To attempt to correct for nonrespondent bias physician respondents were compared to nurse respondents, and the return rates were the same. The response rate for nurses was 17.4% and for physicians it was 17.3%. From these numbers, the percentage of nurses that responded equaled the percentage of physicians that responded. Surveys were distributed to all clinical units; however, demographic profiles of the clinical units are not known. Therefore, it is not possible to correct for nonrespondent bias within the two groups. The study conducted by Menachemi and Brooks (2006), which used the same technology assessment survey, compared responders and nonresponders with respect to known demographics and found “no significant evidence of bias was detected even after employing common techniques used to identify response bias” (p. 85). Results Demographics Study participants included registered nurses (RNs), physician (including employed residents), and other medical professionals such as pharmacists and physical therapists. Of the 337 surveys returned (a 21.4% participation rate), 7 respondents were excluded, 69 respondents (20.9%) reported themselves as physicians, and 220 (66.7%) reported their position as nurse. The final return rate was 21%. The percentage of physicians that responded was equal to the percentage of nurses that responded. Demographic characteristics of the respondents are shown in Table 1. One nonemployed physician completed the survey, and those responses were removed from analysis. In addition, six administrative support staff members that would not use an EMR were excluded. Missing demographic answers were noted on the specific questions and the total respondents revised for that question. Respondents that did not answer or partially answered questions 10 and 17 were excluded from data analysis. The number of respondents for this analysis was adjusted to reflect missing responses. Table 1 Participants’ Demographic Characteristics Category Physicians Nurses Other or unknown Age range: < 35 36 (12%) 79 (26.3%) 2 (0.7%) 35-50 22 (7.3%) 91 (30.3%) 11 (3.7%) > 50 10 (3.3%) 46 (15.3%) 3 (1.0%)
Gender:
Male 35 (11.7%) 26 (8.7%)
Female 33 (11.0%) 189 (63.2%) 16 (5.4%)
Mean yrs. At SJHMC 4.6 (<1 – 33) 8.7 (<1 - 39) 8.3 (<1 - 26)
Mean yrs. since graduation 10.3 (<1 – 48) 12.8 (<1 - 41) 13.2 (<1 - 27)
Descriptive analysis of the demographic data consisted of frequencies and percentages of each variable. The majority of the participants were female (63.2%). More people reported their age range as between 35 and 50 (30.3%).
Barriers to the Use of EMRs
To compare barriers among SJHMC employed medical respondents, chi-square analysis was used, and significance was considered at the p < 0.05 level. Differences existed among physicians, nurses, and other medical staff (see Table 2). For example, no time to learn how to use such a system barrier was dramatically higher for nurses (53.8%) than physicians (34.7%) and other medical staff (18.2%). Another notable differences between nurses and the other groups were system difficulty (50.6% vs. 30% for physicians and 9.1% for other medical staff). Patient confidentiality ranked at 40% for both non-nurse groups, but nurses ranked it at 62.1%. The rank for patient resistance was 43.8% and was considerably lower by physicians (14%) and other medical staff (11.1%). Nurses, more frequently than the other two medical groups, indicated more barriers to using EMR.
Sunday, December 19, 2010
Disaster Management in Healthcare... Summary of Doctoral Research by Sara Geale, Ph.D.
As Chair of the Walden University Dissertation Committee for Sara Geale, Ph.D..I am pleased to share this very brief SUMMARY prepared by Dr. Geale that describes her timely research. My thanks to her for sharing this Summary. Questions or comments may be directed to her at sara.geale@waldenu.edu or sara.geale@aramco.com
Robert E. Hoye, Ph.D.
Summary
A Case Study of a Modular Logistical Systems Approach to
Community Disaster Response
Background
One of the most basic problems with disaster management is the organization and distribution of supplies (Hogan & Burstein, 2007). The shortage of supplies may lead to a situation in which the emergency response is ineffective, and the result is increased human suffering, morbidity, and mortality. Emergency responders agree that it is important to develop strategies to accelerate supply response to deal with unpredictability of demand (Ergun, Karkus, Keskinoca, Swann, & Villarreal, 2010). Supply needs in a disaster situation change significantly according to the type and the phase of the disaster. The supply and demand structure is both complicated and challenging because of the highly unpredictable nature of the time, location, and magnitude. Logistics planning in emergency medical situations involves dispatching needed commodities to the affected areas in a manner that ensures the right resources get to the right places at the right time.
Problem Statement
The problem addressed was how an emergency medical services (EMS) division of a health care organization can best use a logistical or supply management system to meet the changing response needs of multiple-victim emergencies and disasters.
Methodology
A case study was conducted to describe the development of a modular systems approach to community disaster response. Emergency medical responders who were participants in this study identified and discussed a problem in the supply of and dispatch of disaster medical supplies to the scene of an event in a timely, cost-effective manner. A list of likely supplies was compiled and a trial-and-error process used to determine how many patients could be treated with the supplies in a bag that could be easily pulled by one person and lifted into and out of the back of an emergency vehicle. Descriptive case study methodology was used to evaluate the system and consider its effectiveness in the realm within which it operates. The study also considered generalizability of the system to other emergency medical responders.
Results
The results of this case study illustrated that victims of disaster, as well as the responding medical team, benefit from the significantly increased efficiency of the preparedness of the system. Responses can address nearly every contingency and treat a variety of medical emergencies. The system can meet the needs of trauma caused by a variety of disasters and can be scaled up or down to meet the changing needs of the scenario. The system enables greater efficiency for addressing human needs and is structured to efficiently accommodate ongoing refinements.
Conclusion
With disasters on the increase globally, it is important that communities everywhere prepare for them. EMS has long recognized systems in place to deal with day to day emergencies. Disasters, however, overwhelm those established systems. Disaster from a medical perspective is an imbalance of supply and demand. EMS must have systems and process in place that can deal with this imbalance (Auf Der Heide, 2007; Hogan & Burstein, 2007; Perry & Quarantelli, 2005). The modular color-coded bag system is part of planning and preparation for disasters. It is part of the system approach to the management of disasters. Findings showed that prepacking of medical supplies in modular containers for rapid transfer to multiple victim emergencies could increase the effectiveness of the EMS. The implications for positive social change are that a systems approach to disaster management has the potential to reduce morbidity and mortality through effective disaster response at the community level.
References
Auf Der Heide, E. (2007). Disaster response planning and coordination. In D. E. Hogan & J. L. Burstein (Eds.), Disaster Medicine (pp. 95-126). Philadelphia, PA: Wolters Kluwer/Lippincott Williams & Wilkins.
Ergun, O., Karkus, G., Keskinoca, P., Swann, J., & Villarreal, M. (2010). Operations research to improve disaster supply chain management. Retrieved from http://eu.wiley.com
Hogan, D. E., & Burstein, J. L. (2007). Basic perspectives on disaster. In D. E. Hogan & J. L. Burstein (Eds.), Disaster medicine (pp. 1-11). Philadelphia, PA: Lippincott, Williams & Wilkins.
Perry, R. W., & Quarantelli, E. L. (2005). Foreword. In R. W. Perry & E. L. Quarantelli (Eds.). What is a disaster? New answers to old questions (pp. 13-18). Bloomington, IN: Xlibris.
Robert E. Hoye, Ph.D.
Summary
A Case Study of a Modular Logistical Systems Approach to
Community Disaster Response
Background
One of the most basic problems with disaster management is the organization and distribution of supplies (Hogan & Burstein, 2007). The shortage of supplies may lead to a situation in which the emergency response is ineffective, and the result is increased human suffering, morbidity, and mortality. Emergency responders agree that it is important to develop strategies to accelerate supply response to deal with unpredictability of demand (Ergun, Karkus, Keskinoca, Swann, & Villarreal, 2010). Supply needs in a disaster situation change significantly according to the type and the phase of the disaster. The supply and demand structure is both complicated and challenging because of the highly unpredictable nature of the time, location, and magnitude. Logistics planning in emergency medical situations involves dispatching needed commodities to the affected areas in a manner that ensures the right resources get to the right places at the right time.
Problem Statement
The problem addressed was how an emergency medical services (EMS) division of a health care organization can best use a logistical or supply management system to meet the changing response needs of multiple-victim emergencies and disasters.
Methodology
A case study was conducted to describe the development of a modular systems approach to community disaster response. Emergency medical responders who were participants in this study identified and discussed a problem in the supply of and dispatch of disaster medical supplies to the scene of an event in a timely, cost-effective manner. A list of likely supplies was compiled and a trial-and-error process used to determine how many patients could be treated with the supplies in a bag that could be easily pulled by one person and lifted into and out of the back of an emergency vehicle. Descriptive case study methodology was used to evaluate the system and consider its effectiveness in the realm within which it operates. The study also considered generalizability of the system to other emergency medical responders.
Results
The results of this case study illustrated that victims of disaster, as well as the responding medical team, benefit from the significantly increased efficiency of the preparedness of the system. Responses can address nearly every contingency and treat a variety of medical emergencies. The system can meet the needs of trauma caused by a variety of disasters and can be scaled up or down to meet the changing needs of the scenario. The system enables greater efficiency for addressing human needs and is structured to efficiently accommodate ongoing refinements.
Conclusion
With disasters on the increase globally, it is important that communities everywhere prepare for them. EMS has long recognized systems in place to deal with day to day emergencies. Disasters, however, overwhelm those established systems. Disaster from a medical perspective is an imbalance of supply and demand. EMS must have systems and process in place that can deal with this imbalance (Auf Der Heide, 2007; Hogan & Burstein, 2007; Perry & Quarantelli, 2005). The modular color-coded bag system is part of planning and preparation for disasters. It is part of the system approach to the management of disasters. Findings showed that prepacking of medical supplies in modular containers for rapid transfer to multiple victim emergencies could increase the effectiveness of the EMS. The implications for positive social change are that a systems approach to disaster management has the potential to reduce morbidity and mortality through effective disaster response at the community level.
References
Auf Der Heide, E. (2007). Disaster response planning and coordination. In D. E. Hogan & J. L. Burstein (Eds.), Disaster Medicine (pp. 95-126). Philadelphia, PA: Wolters Kluwer/Lippincott Williams & Wilkins.
Ergun, O., Karkus, G., Keskinoca, P., Swann, J., & Villarreal, M. (2010). Operations research to improve disaster supply chain management. Retrieved from http://eu.wiley.com
Hogan, D. E., & Burstein, J. L. (2007). Basic perspectives on disaster. In D. E. Hogan & J. L. Burstein (Eds.), Disaster medicine (pp. 1-11). Philadelphia, PA: Lippincott, Williams & Wilkins.
Perry, R. W., & Quarantelli, E. L. (2005). Foreword. In R. W. Perry & E. L. Quarantelli (Eds.). What is a disaster? New answers to old questions (pp. 13-18). Bloomington, IN: Xlibris.
Monday, December 6, 2010
Principles & Practices of Home Health, Edited by John S. Spratt, MD, Robert E. Hoye, Ph.D. & Rhonda Hawley
Home Health Care: Principles and Practices (CRC Press), Hardcover (1996)
by John Spratt, Robert Hoye, Rhonda Hawley
Hardcover, CRC Press
1996
English
ISBN: 188401593X
ISBN-13: 9781884015939
Twenty-nine practitioners combine their expertise to bring clarity to an issue that is at the forefront of discussion-home health care.The field is emerging and is growing faster than most professionals and their patients can keep up with. Here is a text in which the authors make every effort to provide readers with the latest thinking and technology that can better the home health care field. Spiraling costs have forced all aspects of illnesses to be closely scrutinized for possible home care applications and financial savings.The industry is growing rapidly, fueled by increasing service and constant technological breakthroughs, but the overriding philosophy must be focused on cost containment with maintenance of high quality care. This book is directed at providing highly practical, up-to-date information that health care professionals can use in their daily practices.
by John Spratt, Robert Hoye, Rhonda Hawley
Hardcover, CRC Press
1996
English
ISBN: 188401593X
ISBN-13: 9781884015939
Twenty-nine practitioners combine their expertise to bring clarity to an issue that is at the forefront of discussion-home health care.The field is emerging and is growing faster than most professionals and their patients can keep up with. Here is a text in which the authors make every effort to provide readers with the latest thinking and technology that can better the home health care field. Spiraling costs have forced all aspects of illnesses to be closely scrutinized for possible home care applications and financial savings.The industry is growing rapidly, fueled by increasing service and constant technological breakthroughs, but the overriding philosophy must be focused on cost containment with maintenance of high quality care. This book is directed at providing highly practical, up-to-date information that health care professionals can use in their daily practices.
Sunday, December 5, 2010
Number of U.S. residents without health insurance at new high
FOR YOUR RESEARCH... From the Kaiser Health News: September 16, 2010
Number of U.S. residents without health insurance at new high
A reflection of the weak economy, experts say
By Phil Galewitz, Andrew Villegas
Thursday, September 16, 2010
WASHINGTON, D.C. — In a reflection of the battered economy, the number of people without health insurance rose sharply last year to 50.7 million — an all time high — according to data released Thursday by the Census Bureau.
That pushed the rate of uninsured Americans to 16.7 percent last year from 15.4 percent in 2008, when there were 46.3 million uninsured. It was one of the largest single year increases since the Census starting tracking the figure in 1987.
Nearly every demographic and geographic group posted a rise in the uninsured rate — with the exception of children, who remained stable at about 10 percent. The sharpest jumps were in the Midwest and South, although all areas of the country saw increases.
Jim McLean’s KPR report on the increase in uninsured Kansans
"In a word this is devastating," said Jonathan Oberlander, professor of social medicine and health policy at the University of North Carolina-Chapel Hill.
Both Democrats and Republicans hoped to gain public support from the new figures. The surge in the uninsured could help Democrats gain more support for the new health overhaul law because it underscores the need for dramatically changing the health system. But at the same time, Republicans calling for repeal of that law can use the report to blame Democrats for failing to fix the economy.
"Though not surprising, the uninsured numbers do indicate the role of the dismal economy," said Joseph Antos, a health policy expert from the conservative American Enterprise Institute. "Health insurance is really secondary to the economy."
Although in the short term the report could hurt Democrats, the higher number of uninsured should make it harder for Republicans to talk about repealing the health law, said Oberlander.
"From a political standpoint," he said, "the report makes the administration's and Democrats' point that the status quo is not sustainable and underscores why you needed to do something to stabilize insurance."
The health law approved in March mandates that nearly all Americans have health insurance. It would provide coverage to 32 million more Americans starting in 2014 as the state-federal Medicaid program is expanded and lower-income people get government subsidies to buy coverage through new insurance exchanges or marketplaces.
The jump in uninsured last year reflects the worsening recession, which started in 2008 but ravaged the economy in 2009. The unemployment rate rose to 9.3 percent in 2009 from 5.8 percent in 2008.
"A lot of it is due to changes in people's employment status as people moved from full time to part time and from working to not working," said David Johnson, chief of the housing and household economic statistics division at the Census Bureau.
Analysts said they were not surprised by the big increase in uninsured.
"We've reached yet another milestone in the number of uninsured," said Peter Cunningham, senior fellow at the Center for Studying Health System Change, an independent, nonpartisan think tank. "It's not surprising because it's being driven almost entirely by a big drop in people with private coverage and employer-sponsored coverage."
The percentage of people covered by employer-sponsored coverage dropped to 55.8 percent last year from 58.5 percent in 2008.
The Census report showed there were 43.6 million people in poverty in 2009, up from 39.8 million in 2008 — the third consecutive annual increase.
"The numbers are heartbreaking," said Sara Rosenbaum, a professor of health law and policy at George Washington University. "If we needed any more evidence of the absolute imperative of health reform, this is it."
Indeed, the reliance in America on an employer-based delivery system for health coverage means that the population is susceptible to such explosions of the number of uninsured when unemployment increases, Rosenbaum added. Often, Medicaid — meant to provide coverage for the nation's poor — can't cover many of these newly uninsured, she explained, because strict qualifications exclude many middle class families who lose their jobs and take unemployment benefits.
And it may not get better anytime soon. Rosenbaum said that there will probably be at least one more year with "terrible" health insurance numbers as the economy lags and employers continue to lay workers off.
The report also found that nearly a third of Americans — about 93 million — are now covered by government insurance, mainly Medicare and Medicaid. While the numbers of people on Medicare remains stable, the percentage of people covered by Medicaid, the federal-state program for people with low incomes, rose from to 15.7 percent of Americans from 14.1 percent. Nearly 48 million Americans are in Medicaid programs.
Given the sharp divide in public opinion of the new health law, many Democrats have been reluctant to talk about the health law on the campaign trail. That probably won't change, even with these new figures, said Ross Baker, a professor of political science at Rutgers University.
"They're not going to go back to it. If they've run [from the new law in their campaigns] they're not going to pull a U-turn and embrace it." And voters, Baker said, are unlikely to be more receptive to health reform now because they still simply don't understand what it means for them.
Indeed, the other danger for Democrats going into November's midterm elections is that "any bad stat is going to reflect poorly on the incumbent," Baker said.
Amber Hergen, 34, of Los Angeles, is one of those Americans who lost coverage last year. She left her publicity job at a marketing company, where she had insurance, to pursue her dream of becoming an actress. She's been unable to find affordable individual coverage.
She learned the risk of being uninsured last month when she went to the emergency room after accidentally ingesting a household cleaner. Though she was at the hospital less than an hour, her bill was $2,500.
"Being without insurance is kind of like walking on a tightrope without a net," she said. "It's scary."
Kaiser Health News (KHN) is a nonprofit news organization committed to in-depth coverage of health care policy and politics. The Washington, D.C.-based news service is a partner of KHI News Service.
Number of U.S. residents without health insurance at new high
A reflection of the weak economy, experts say
By Phil Galewitz, Andrew Villegas
Thursday, September 16, 2010
WASHINGTON, D.C. — In a reflection of the battered economy, the number of people without health insurance rose sharply last year to 50.7 million — an all time high — according to data released Thursday by the Census Bureau.
That pushed the rate of uninsured Americans to 16.7 percent last year from 15.4 percent in 2008, when there were 46.3 million uninsured. It was one of the largest single year increases since the Census starting tracking the figure in 1987.
Nearly every demographic and geographic group posted a rise in the uninsured rate — with the exception of children, who remained stable at about 10 percent. The sharpest jumps were in the Midwest and South, although all areas of the country saw increases.
Jim McLean’s KPR report on the increase in uninsured Kansans
"In a word this is devastating," said Jonathan Oberlander, professor of social medicine and health policy at the University of North Carolina-Chapel Hill.
Both Democrats and Republicans hoped to gain public support from the new figures. The surge in the uninsured could help Democrats gain more support for the new health overhaul law because it underscores the need for dramatically changing the health system. But at the same time, Republicans calling for repeal of that law can use the report to blame Democrats for failing to fix the economy.
"Though not surprising, the uninsured numbers do indicate the role of the dismal economy," said Joseph Antos, a health policy expert from the conservative American Enterprise Institute. "Health insurance is really secondary to the economy."
Although in the short term the report could hurt Democrats, the higher number of uninsured should make it harder for Republicans to talk about repealing the health law, said Oberlander.
"From a political standpoint," he said, "the report makes the administration's and Democrats' point that the status quo is not sustainable and underscores why you needed to do something to stabilize insurance."
The health law approved in March mandates that nearly all Americans have health insurance. It would provide coverage to 32 million more Americans starting in 2014 as the state-federal Medicaid program is expanded and lower-income people get government subsidies to buy coverage through new insurance exchanges or marketplaces.
The jump in uninsured last year reflects the worsening recession, which started in 2008 but ravaged the economy in 2009. The unemployment rate rose to 9.3 percent in 2009 from 5.8 percent in 2008.
"A lot of it is due to changes in people's employment status as people moved from full time to part time and from working to not working," said David Johnson, chief of the housing and household economic statistics division at the Census Bureau.
Analysts said they were not surprised by the big increase in uninsured.
"We've reached yet another milestone in the number of uninsured," said Peter Cunningham, senior fellow at the Center for Studying Health System Change, an independent, nonpartisan think tank. "It's not surprising because it's being driven almost entirely by a big drop in people with private coverage and employer-sponsored coverage."
The percentage of people covered by employer-sponsored coverage dropped to 55.8 percent last year from 58.5 percent in 2008.
The Census report showed there were 43.6 million people in poverty in 2009, up from 39.8 million in 2008 — the third consecutive annual increase.
"The numbers are heartbreaking," said Sara Rosenbaum, a professor of health law and policy at George Washington University. "If we needed any more evidence of the absolute imperative of health reform, this is it."
Indeed, the reliance in America on an employer-based delivery system for health coverage means that the population is susceptible to such explosions of the number of uninsured when unemployment increases, Rosenbaum added. Often, Medicaid — meant to provide coverage for the nation's poor — can't cover many of these newly uninsured, she explained, because strict qualifications exclude many middle class families who lose their jobs and take unemployment benefits.
And it may not get better anytime soon. Rosenbaum said that there will probably be at least one more year with "terrible" health insurance numbers as the economy lags and employers continue to lay workers off.
The report also found that nearly a third of Americans — about 93 million — are now covered by government insurance, mainly Medicare and Medicaid. While the numbers of people on Medicare remains stable, the percentage of people covered by Medicaid, the federal-state program for people with low incomes, rose from to 15.7 percent of Americans from 14.1 percent. Nearly 48 million Americans are in Medicaid programs.
Given the sharp divide in public opinion of the new health law, many Democrats have been reluctant to talk about the health law on the campaign trail. That probably won't change, even with these new figures, said Ross Baker, a professor of political science at Rutgers University.
"They're not going to go back to it. If they've run [from the new law in their campaigns] they're not going to pull a U-turn and embrace it." And voters, Baker said, are unlikely to be more receptive to health reform now because they still simply don't understand what it means for them.
Indeed, the other danger for Democrats going into November's midterm elections is that "any bad stat is going to reflect poorly on the incumbent," Baker said.
Amber Hergen, 34, of Los Angeles, is one of those Americans who lost coverage last year. She left her publicity job at a marketing company, where she had insurance, to pursue her dream of becoming an actress. She's been unable to find affordable individual coverage.
She learned the risk of being uninsured last month when she went to the emergency room after accidentally ingesting a household cleaner. Though she was at the hospital less than an hour, her bill was $2,500.
"Being without insurance is kind of like walking on a tightrope without a net," she said. "It's scary."
Kaiser Health News (KHN) is a nonprofit news organization committed to in-depth coverage of health care policy and politics. The Washington, D.C.-based news service is a partner of KHI News Service.
Tuesday, November 30, 2010
The Problem with Free Market Health Care
The Problem with Free Market Health Care
By Joe Flower
The right payment structure keeps patients healthy while saving money.
Complete credit is given to the author... Joe Flower... for this insightful article.
Joe Flower is a health care futurist, speaker and founder of Imagine What If, a service of the education firm The Change Project Inc. Flower is also a regular contributor to H&HN Weekly and a member of Health Forum's Forum Faculty Speaker Service.
This article 1st appeared on November 29, 2010 in HHN Magazine online site.
We want health care to be abundant, effective, easy and cheap; for too many of us, too much of the time, it is scarce, ineffective and maddeningly difficult. For all of us, it is far too expensive. Why? How did we get in this mess? How do we end up paying so much for health care and not getting what we want?
It's a big question, and it's at the core of the mess we are in. The convoluted way we pay for health care in the United States gives too many patients treatments they don't need, or treats them for conditions that could have been prevented with much cheaper care, or denies patients services they need. How does this happen?
To answer this question, we have to dig into the actual structures of health care and some of the basics of economics. And in that answer we can begin to see how we need to rebuild those very structures to survive and thrive beyond reform.
Why Doesn't Competition Seem to Work in Health Care?
There certainly seems to be plenty of competition. For example, there are:
thousands of hospitals of different types (for-profit and nonprofit, freestanding and chain, general and specialty, teaching, children's, public and private, military and veterans);
hundreds of thousands of doctors in specialties organized every way you could imagine (solo practice, small practice, large multispecialty practice, working for hospitals and health systems, running their own centers, in cooperatives like Group Health of Puget Sound and staff-model HMOs like Kaiser);
hundreds of health insurers;
scores of pharmaceutical companies, device manufacturers and other health care vendors supplying bed pans, gurneys and ambulances; and
thousands of pharmacy benefit managers, vendor certification companies, disease management agencies, consultants and other companies providing bits of outsourced management expertise.
Though there is plenty of regulation, on most levels of the system there is no central Soviet-style commission allocating resources and deciding who gets which customers. All these organizations are free to compete for the customers' dollars.
Why, with all that competition, can't most of us seem to get the health care we need when we need it, where we need it, at a reasonable price? For most Americans, though we can see that modern medicine offers a nearly miraculous plethora of cures and therapies, our access to it through the health care industry is often arbitrary, sometimes so arbitrary as to be cruel. For those younger than 65, the price is often so high that even insured people can be one serious disease or traffic accident away from permanent poverty. And even when it works, it can be mind-blowingly inconvenient.
How can that be? How can a "free-market" system so blatantly fail to serve its customers? Until we find the answer, we will never be able to find our way out of this mess. Let's do a little basic analysis, a little Health Care Economics 101.
What Does the Customer Want?
What do I really want, as a customer of health care? Realistically, four things:
When I'm sick, fix me.
If you can't fix it, help me manage it.
When I am well, help me stay well.
Be there when I really need you.
Why is it so hard for me to get those four things? Because—here's the big key—I'm not really the customer. In fact, in most of health care, it can be hard to tell who really is the customer.
Who Is the Customer?
What's a customer? Customers decide that they want something, choose it and pay for it. You decide that a new TV would be nice. You look online or go to a big box store, maybe check out a local independent store. You find what seems a reasonable value for your money and you plunk down a credit card. You're a customer.
The customer is the key regulating part of any free-market system. The customer is the reason you never see a plate of scrambled eggs or a new car advertised for $1,000. It's the customer that enforces all sense of value.
So what's different between classic economics and health care economics? Classic economics pictures a buyer and a seller. There is a constant, dynamic feedback loop between the many buyers and sellers in a market that establishes not only what things cost, but even what's offered for sale, and on what kind of terms.
The core driver of all health care economics is the utilization decision, that is, people deciding to make use of some health care service. They get a new hip, take a new drug, get an exam, go in for a mammogram. The great majority of health care is insurance-supported, whether through government insurance, such as Medicare, or through employers' private insurance. And the great majority of health care is provided fee-for-service, that is, the health care provider (the doctor or hospital) bills the insurance payer for each separate test, procedure or prescription.
So what happens to that feedback loop in health care? First of all, the buyer is split in two—into a chooser and a payer. The organization that pays the bill does not make the decision to use that particular service. So the feedback loop between buyer and seller is obscured. And the chooser and the payer have quite different agendas. If the payer is just there to pay, it can have only one goal: to pay as little as it can get away with. It might set rules and payment schedules, but can never quite get it right, since it is really not there in the transaction, making the choice.
It begins to get cloudy: Who is the chooser? Who is deciding to use the service? Again there's a split. The chooser is not the patient alone, but the patient (or the patient's family) in consultation with the provider (usually the doctor). So again, and in a different way, the buyer is split. And the patient and the provider have different stances. The patient has enormous "skin in the game"—great incentive to use whatever services might seem to help, since it's the patient's body, his pain, indeed, often his life or death that is on the line. The provider, on the other hand, has almost all the resources: the knowledge, expertise, equipment and access to drugs and therapies. In any given transaction, the provider has far less skin in the game—the patient is one of hundreds or thousands, so the feedback loop gets even more obscured and tortuous.
It grows murkier: Who is the "seller?" Who is providing the service being sold? In most instances, it is the provider. The doctor who is advising the patient on buying the service is often either providing the service or working for the organization that will provide the service—or even owns it. You need a new knee, but you're in luck. You've come to the right place, because I am an expert knee installer. And the seller, of course, has a completely different agenda from the buyer. The seller's agenda is simply to sell as much as possible. So the feedback loop between buyer and seller becomes so tortuous and knotted as to be useless, and the system skews, as a normal part of doing business, toward selling the services that make the most money.
It is inescapable; you will serve somebody. If it is not the patient, it will be somebody else.
Out of this we get markets in which, for instance, it can be very hard for a Medicaid recipient with diabetes to get (or even hear about) the nutritional counseling that might help her save her feet, but quite easy to get a surgeon to amputate her feet when her diabetes destroys them.
What Are Health Care Providers Paid to Do?
This may sound overly cynical. Many doctors would protest that they never offer a service just because it would make them more money. But, as one neurologist put it to me, "The more I care about my work, the less money I make. The way for me to make more money is to serve my patients less—give them less time and attention and cut them loose as soon as possible." That's a terrible bind in which to put our best medical minds. Many doctors doubtless choose the path this doctor does: Do better work and make less money. But many doctors feel forced to make the other choice: Do poorer work and make more money.
It is important to remember the two core rules of economics:
People do what they are paid to do.
People do exactly what they are paid to do.
People notice in exquisite detail what makes them money and brings them success. As a normal practice, they will not do things that cost them money or risk getting them into trouble. In health care, what brings a provider money and success is doing more of the procedures and tests that are well-compensated by payers, and doing fewer or none of those that are not well-compensated—and certainly never failing to do a test or procedure that might keep them out of a malpractice suit, whether the patient really needs it or not. And those well-compensated and malpractice-safe procedures and tests are only indirectly related to the four things we really want when we think we are the customer. Almost no one in health care is directly paid to give us what we actually want.
What's the Structure?
It's important to notice that this confusion is structural. The ordinary structures of health care, with doctors, clinics and hospitals in strict fee-for-service relationships with payers, have great difficulty acting as if the patient is a customer.
If we are to get out of this mess, we need to tweak those old structures and build new ones. That's why we are seeing fascinating, weird experimental structures arising across health care—"extended medical home" physician-hospital organizations, "virtual accountable care organizations" like those I cited in my last column. And that is why almost all of these are new forms of partnerships, ad hoc contractual relationships that cut across the traditional structural lines to deal with the health of particular populations. The contracts set up incentive relationships that guarantee someone makes a profit specifically by tending to the real needs of the patient, not just by providing services to the patient. And they are all over the place, taking different shapes to fill niches in the vast ecology of health care.
Let me give you one example. If you were to look around, as an entrepreneur, for a way to make money by helping some population be healthier, what populations would seem like the "low-hanging fruit"? Would you think, "Ah, yes! Frail, elderly people on Medicaid in state-supported convalescent homes! And kids with disabilities on Medicaid!" Probably not. And yet that is exactly what happened in Illinois. McKesson's disease management subsidiary contracted with the state to provide its Your Healthcare Plus services to just such populations. Teams of doctors, nurses and case managers, many of them on-site across the state, working with the patients' existing providers, measurably improved the health of these patients. Counting the costs and fees for running the program, McKesson saved the state of Illinois $307 million in the first three years of the program by giving people more services of the right kind of care and attention, not less.
Hospitals can form these OWAs ("other weird arrangements") in all kinds of shapes, from at-risk contracts with insurers or CMS, to shared-risk, medical-home arrangements with physician-hospital organizations, to disease-management contracts with government agencies. And increasingly they are, across the country, because in the new environment the overburden of high cost and low capacity is killing us. We simply must find more efficient and more effective ways of serving our customers.
Structure matters. With the right structure, you make money by saving money. You help the customers meet their objectives, and you get paid for it.
Joe Flower is a health care futurist, speaker and founder of Imagine What If, a service of the education firm The Change Project Inc. Flower is also a regular contributor to H&HN Weekly and a member of Health Forum's Forum Faculty Speaker Service.
This article 1st appeared on November 29, 2010 in HHN Magazine online site.
By Joe Flower
The right payment structure keeps patients healthy while saving money.
Complete credit is given to the author... Joe Flower... for this insightful article.
Joe Flower is a health care futurist, speaker and founder of Imagine What If, a service of the education firm The Change Project Inc. Flower is also a regular contributor to H&HN Weekly and a member of Health Forum's Forum Faculty Speaker Service.
This article 1st appeared on November 29, 2010 in HHN Magazine online site.
We want health care to be abundant, effective, easy and cheap; for too many of us, too much of the time, it is scarce, ineffective and maddeningly difficult. For all of us, it is far too expensive. Why? How did we get in this mess? How do we end up paying so much for health care and not getting what we want?
It's a big question, and it's at the core of the mess we are in. The convoluted way we pay for health care in the United States gives too many patients treatments they don't need, or treats them for conditions that could have been prevented with much cheaper care, or denies patients services they need. How does this happen?
To answer this question, we have to dig into the actual structures of health care and some of the basics of economics. And in that answer we can begin to see how we need to rebuild those very structures to survive and thrive beyond reform.
Why Doesn't Competition Seem to Work in Health Care?
There certainly seems to be plenty of competition. For example, there are:
thousands of hospitals of different types (for-profit and nonprofit, freestanding and chain, general and specialty, teaching, children's, public and private, military and veterans);
hundreds of thousands of doctors in specialties organized every way you could imagine (solo practice, small practice, large multispecialty practice, working for hospitals and health systems, running their own centers, in cooperatives like Group Health of Puget Sound and staff-model HMOs like Kaiser);
hundreds of health insurers;
scores of pharmaceutical companies, device manufacturers and other health care vendors supplying bed pans, gurneys and ambulances; and
thousands of pharmacy benefit managers, vendor certification companies, disease management agencies, consultants and other companies providing bits of outsourced management expertise.
Though there is plenty of regulation, on most levels of the system there is no central Soviet-style commission allocating resources and deciding who gets which customers. All these organizations are free to compete for the customers' dollars.
Why, with all that competition, can't most of us seem to get the health care we need when we need it, where we need it, at a reasonable price? For most Americans, though we can see that modern medicine offers a nearly miraculous plethora of cures and therapies, our access to it through the health care industry is often arbitrary, sometimes so arbitrary as to be cruel. For those younger than 65, the price is often so high that even insured people can be one serious disease or traffic accident away from permanent poverty. And even when it works, it can be mind-blowingly inconvenient.
How can that be? How can a "free-market" system so blatantly fail to serve its customers? Until we find the answer, we will never be able to find our way out of this mess. Let's do a little basic analysis, a little Health Care Economics 101.
What Does the Customer Want?
What do I really want, as a customer of health care? Realistically, four things:
When I'm sick, fix me.
If you can't fix it, help me manage it.
When I am well, help me stay well.
Be there when I really need you.
Why is it so hard for me to get those four things? Because—here's the big key—I'm not really the customer. In fact, in most of health care, it can be hard to tell who really is the customer.
Who Is the Customer?
What's a customer? Customers decide that they want something, choose it and pay for it. You decide that a new TV would be nice. You look online or go to a big box store, maybe check out a local independent store. You find what seems a reasonable value for your money and you plunk down a credit card. You're a customer.
The customer is the key regulating part of any free-market system. The customer is the reason you never see a plate of scrambled eggs or a new car advertised for $1,000. It's the customer that enforces all sense of value.
So what's different between classic economics and health care economics? Classic economics pictures a buyer and a seller. There is a constant, dynamic feedback loop between the many buyers and sellers in a market that establishes not only what things cost, but even what's offered for sale, and on what kind of terms.
The core driver of all health care economics is the utilization decision, that is, people deciding to make use of some health care service. They get a new hip, take a new drug, get an exam, go in for a mammogram. The great majority of health care is insurance-supported, whether through government insurance, such as Medicare, or through employers' private insurance. And the great majority of health care is provided fee-for-service, that is, the health care provider (the doctor or hospital) bills the insurance payer for each separate test, procedure or prescription.
So what happens to that feedback loop in health care? First of all, the buyer is split in two—into a chooser and a payer. The organization that pays the bill does not make the decision to use that particular service. So the feedback loop between buyer and seller is obscured. And the chooser and the payer have quite different agendas. If the payer is just there to pay, it can have only one goal: to pay as little as it can get away with. It might set rules and payment schedules, but can never quite get it right, since it is really not there in the transaction, making the choice.
It begins to get cloudy: Who is the chooser? Who is deciding to use the service? Again there's a split. The chooser is not the patient alone, but the patient (or the patient's family) in consultation with the provider (usually the doctor). So again, and in a different way, the buyer is split. And the patient and the provider have different stances. The patient has enormous "skin in the game"—great incentive to use whatever services might seem to help, since it's the patient's body, his pain, indeed, often his life or death that is on the line. The provider, on the other hand, has almost all the resources: the knowledge, expertise, equipment and access to drugs and therapies. In any given transaction, the provider has far less skin in the game—the patient is one of hundreds or thousands, so the feedback loop gets even more obscured and tortuous.
It grows murkier: Who is the "seller?" Who is providing the service being sold? In most instances, it is the provider. The doctor who is advising the patient on buying the service is often either providing the service or working for the organization that will provide the service—or even owns it. You need a new knee, but you're in luck. You've come to the right place, because I am an expert knee installer. And the seller, of course, has a completely different agenda from the buyer. The seller's agenda is simply to sell as much as possible. So the feedback loop between buyer and seller becomes so tortuous and knotted as to be useless, and the system skews, as a normal part of doing business, toward selling the services that make the most money.
It is inescapable; you will serve somebody. If it is not the patient, it will be somebody else.
Out of this we get markets in which, for instance, it can be very hard for a Medicaid recipient with diabetes to get (or even hear about) the nutritional counseling that might help her save her feet, but quite easy to get a surgeon to amputate her feet when her diabetes destroys them.
What Are Health Care Providers Paid to Do?
This may sound overly cynical. Many doctors would protest that they never offer a service just because it would make them more money. But, as one neurologist put it to me, "The more I care about my work, the less money I make. The way for me to make more money is to serve my patients less—give them less time and attention and cut them loose as soon as possible." That's a terrible bind in which to put our best medical minds. Many doctors doubtless choose the path this doctor does: Do better work and make less money. But many doctors feel forced to make the other choice: Do poorer work and make more money.
It is important to remember the two core rules of economics:
People do what they are paid to do.
People do exactly what they are paid to do.
People notice in exquisite detail what makes them money and brings them success. As a normal practice, they will not do things that cost them money or risk getting them into trouble. In health care, what brings a provider money and success is doing more of the procedures and tests that are well-compensated by payers, and doing fewer or none of those that are not well-compensated—and certainly never failing to do a test or procedure that might keep them out of a malpractice suit, whether the patient really needs it or not. And those well-compensated and malpractice-safe procedures and tests are only indirectly related to the four things we really want when we think we are the customer. Almost no one in health care is directly paid to give us what we actually want.
What's the Structure?
It's important to notice that this confusion is structural. The ordinary structures of health care, with doctors, clinics and hospitals in strict fee-for-service relationships with payers, have great difficulty acting as if the patient is a customer.
If we are to get out of this mess, we need to tweak those old structures and build new ones. That's why we are seeing fascinating, weird experimental structures arising across health care—"extended medical home" physician-hospital organizations, "virtual accountable care organizations" like those I cited in my last column. And that is why almost all of these are new forms of partnerships, ad hoc contractual relationships that cut across the traditional structural lines to deal with the health of particular populations. The contracts set up incentive relationships that guarantee someone makes a profit specifically by tending to the real needs of the patient, not just by providing services to the patient. And they are all over the place, taking different shapes to fill niches in the vast ecology of health care.
Let me give you one example. If you were to look around, as an entrepreneur, for a way to make money by helping some population be healthier, what populations would seem like the "low-hanging fruit"? Would you think, "Ah, yes! Frail, elderly people on Medicaid in state-supported convalescent homes! And kids with disabilities on Medicaid!" Probably not. And yet that is exactly what happened in Illinois. McKesson's disease management subsidiary contracted with the state to provide its Your Healthcare Plus services to just such populations. Teams of doctors, nurses and case managers, many of them on-site across the state, working with the patients' existing providers, measurably improved the health of these patients. Counting the costs and fees for running the program, McKesson saved the state of Illinois $307 million in the first three years of the program by giving people more services of the right kind of care and attention, not less.
Hospitals can form these OWAs ("other weird arrangements") in all kinds of shapes, from at-risk contracts with insurers or CMS, to shared-risk, medical-home arrangements with physician-hospital organizations, to disease-management contracts with government agencies. And increasingly they are, across the country, because in the new environment the overburden of high cost and low capacity is killing us. We simply must find more efficient and more effective ways of serving our customers.
Structure matters. With the right structure, you make money by saving money. You help the customers meet their objectives, and you get paid for it.
Joe Flower is a health care futurist, speaker and founder of Imagine What If, a service of the education firm The Change Project Inc. Flower is also a regular contributor to H&HN Weekly and a member of Health Forum's Forum Faculty Speaker Service.
This article 1st appeared on November 29, 2010 in HHN Magazine online site.
Friday, October 15, 2010
ISSUES FACING HEALTHCARE
Source: HHN Magazine, Sept. 2009... Credit to Mary Grayson
The Root of the Problem
The issues facing health care are immense, but AHA Chair-Elect John Bluford believes that common sense will prevail in the end.
as told to Mary Grayson
Many of our systemic health care delivery system ills cannot be cured by legislation. The real revolution will come to health care when we reach a culture of wellness and prevention, says John Bluford, president and CEO of Truman Medical Centers, Kansas City, Mo., and the new chair-elect of the American Hospital Association.
Health care service is a family affair for me. I had many uncles in health care and my grandfather was a dentist. I went to Fisk University in Nashville majoring in pre-med and I was on my way to Meharry Medical School when a recruiter for Northwestern University's business program interviewed me. The gentleman tried to convince me that I ought to go into business because of my orientation toward extracurricular activities and leadership roles with my fraternity, student government and the basketball team at Fisk. I told him I knew nothing about business administration, but I passed the graduate school test and received a full two-year scholarship at Northwestern sponsored by what was then the United Insurance Company in Chicago, plus a $250 monthly stipend. In 1971, that was good spending money. So I enrolled in the business school with a hospital and health services major. The real hook was when I realized that you don't have to be a doctor to work in a hospital. You can lead a variety of activities that help support many doctors and their patients in an administrative role.
My first job in graduate school was at the 3,000-bed Cook County Hospital. As an administrative resident, I was the weekend administrator under Bill Silverman and Bob Shakno, both of whom came from Michael Reese Medical Center to help turn around Cook County Hospital in the early '70s. This was a very turbulent time at that county hospital, following much-publicized strikes by residents and nurses. After graduating from Northwestern, I took over as the night administrator. It was training under fire, but the beauty of it for me was that on weekends and nights, I had overall administrative responsibility for the hospital.
I have many stories after being the night administrator at Cook County. My favorite is the night I was looking at the surveillance television monitor and saw one of our buildings on fire. About 16 buildings comprised the Cook County campus and the psych hospital was on fire. I had Bob Shakno's home phone number. He always said, "If there are any problems, just call me." Well tonight was the night. His response: "Step No. 1: Call the fire department."
Today's Non-System
The business we're in today is very complex and often contradictory. We're rewarded for sickness but not wellness and prevention. So many component parts create this non-system—insurers, physicians, hospitals, pharma, device manufacturers—and each component part represents a competing interest that resists change. The cost of health care is a big issue and we all want to reduce cost. But someone's cost is someone else's revenue. Therein lies the root of many of the health care reform political battles inherent in moving the system forward. That is why I am so pleased with AHA's Health for Life platform (coverage, wellness, efficiency, highest quality and best information) as it takes a comprehensive look at the total system(s) for reform.
Today, many uninsured people lack access to appropriate care, at the appropriate time and the appropriate place. One way of thinking is that sick people don't need insurance; what they need is appropriate access to health care. Today, they often access health care through safety-net hospitals and emergency departments, where ongoing continuity of care may suffer. Appropriate health care reform, which increases appropriate access to services, may not be cheaper in the short run, but we might have a healthier society and other benefits to the common good.
The long-term key to success is the prevention of illness and managing the costs associated with sickness. A rallying cry around the country in support of lifestyle enhancement, physical fitness and good nutrition would be the biggest enhancement to health care reform that we could achieve from a quality-of-life perspective.
End-of-life care counseling can also have long-term results. Evidence already exists that a 90-year-old with multiple system failure can either stay in a highly intensified, technological ICU environment and have dozens, if not hundreds, of tests done by high-profile professionals for weeks or that person can go home and be treated with dignity and surrounded by loved ones. The irony is that the length of life is the same in either situation. But the choice for quality of life is a no-brainer. We are often incentivized to do more expensive yet less effective modalities. Unfortunately, end-of-life care issues were avoided in the current reform legislation, but eventually the collective American community must discuss it.
Societal Disparities
My 30-plus years in health care have been in the public or safety-net hospital environments that, on the whole, cater to a vulnerable patient population with a high degree of health care disparity. Their condition often represents social disparities—not just health care disparities. Ethnic and racial disparities come into play as well; but broadly speaking it encompasses the people with fewer employment opportunities, sometimes with poor family support, inadequate housing, and this aggregate population crosses all racial and ethnic boundaries. Much of the reform debate in terms of access and cost is really about this vulnerable patient population. If we focused our attention here and society provided resources to solve the underlying problems, we could carry health care reform further than any legislation.
The focus on continuity of care, medical home experiments and advocacy issues play neatly into helping us get our arms around the problem. Many of our clientele have chronic diseases that are not managed well, and they don't have system navigators to get patients from point A to point B to make sure they keep their appointments, manage medications, and so on. And in many cases, the people who treat them can't associate or identify with them to the extent that it takes to overcome or break through the social disparity aspects of their lives.
Research comes into play, but so does common sense. I get frustrated with "process" versus common sense and the prompt execution of good ideas. There sometimes needs to be a greater sense of urgency and balance between research, process and action. If we know that asthma is a problem for a pediatric patient who repeatedly comes to the emergency room, then someone needs to go to the home and find out what's going on in that environment that is creating the problem.
We are about to start a program at Truman Medical Centers that we call Passport to Wellness, which is targeted at our "frequent flyers"—those people who are constantly readmitted, who make a dozen or more visits a month to our emergency room, and have chronic diseases such as diabetes, hypertension, asthma, chronic heart failure. We want to identify about 100 of these patients and provide as much intense case management attention as possible to see if we can solve their issues.
Sometimes we need to think about different types of interventions in dealing with vulnerable patient populations. I was talking with the head of our EMS system about Passport to Wellness and he said, "I see some of these patients 20 to 25 times a month. Many are diabetic and they need medications and some basic assessment. They call us because they know that if they come in by ambulance they will come through the emergency entrance and won't have to wait two or three hours in the waiting room." Bingo. Why not use these talented, skilled emergency medicine service workers? They are at the house, they can administer the medicine, and in many cases they know the patient better than the rest of the health care system. Perversely, we would lose Medicare payment for a full run to the hospital, but the economical, simple thing to do may be to let the EMS workers meet the needs of the patient on the spot.
The whole mental health sector needs to be brought into play as well. A great proportion of the vulnerable patient population has either mental health or addictive behavioral problems. Also, many people who are incarcerated should probably be in a mental health institution, as should many of our homeless. Our society has not opened our eyes to those realities yet.
All of the significant mental health, psychological-related issues and clinical issues associated with behavioral health are upon us. It is a slightly different business than running an acute care hospital. It is often not a money-making proposition. The capacity is woefully low. But it needs to be addressed.
Safety-net hospitals are critical to the communities they serve, not just because they tend to serve the vulnerable and disadvantaged population; safety nets are not merely for the downtrodden. Safety-net hospitals provide services such as Level 1 trauma units, high-risk neonatal units, burn units, oral health, and teaching and training programs that are vitally important to the entire community and may not be available in other parts of that community's delivery system.
They are also major business entities. We hire a lot of people. Safety nets pay lots of payroll tax and contribute significantly to the local economy through the acquisition of supplies, commodities, construction projects and so on. And because most safety-net hospitals are in the urban core, it is even more critical that they continue to be one of the major engines fueling that inner-city economy.
The maintenance and survival of these institutions is an economic issue as much as it is a health care issue.
Unintended Consequences
There is no question that there will be unintended consequences all over the map as the reform process runs its course over many years. It took more than a generation for us to get into our current circumstance in regards to cost, value and quality, and it is going to take some time for us to find our way out. Whatever happens with health care reform legislation today, it will be constantly modified over the next 10 years until we have a system that is more resourceful and meets more needs than the system does today, at a reasonable and affordable cost.
A theme in this year's discussions is that hospital environments with employed physicians, such as Mayo and the Cleveland Clinic, have better continuity of care, better results and run more efficiently and effectively. The physicians and the hospital are not working at cross purposes with cross incentives. In most institutions, the hospital and the physicians are legally independent organizations, but they are connected at the hip financially; one can't move successfully without the other. The new world order through health care reform with strong disease management, bundled payments and gainsharing arrangements should lead us in more unified alignment.
There are two things that create problems for chief executive officers. One is ineffective relationships with physicians and the other involves poor decisions or implementation of major IT projects. Today, the electronic health record is top of mind. And it will benefit the system, patients and clinicians, but it is not the silver bullet. Migrating from paper records to electronic documentation is very difficult and expensive. Without a thorough operational audit of user requirements and fixing the problems in the manual process before automating simply means that you get bad processes faster.
Another element that is critical to hospitals' long-term success is high-performance governance. Qualified trustees who are engaged and buy into the mission of the institution will advocate for that mission throughout the community at large. One of management's responsibilities with the board is not merely answering the questions that they ask as truthfully and honestly as you can but also, in some cases, showing them what questions to ask because often they don't know. That kind of openness and transparency in governance makes for a much stronger institution and across the nation will lead to a much stronger health care delivery system.
This article 1st appeared in the December 2009 issue of HHN Magazine.
The Root of the Problem
The issues facing health care are immense, but AHA Chair-Elect John Bluford believes that common sense will prevail in the end.
as told to Mary Grayson
Many of our systemic health care delivery system ills cannot be cured by legislation. The real revolution will come to health care when we reach a culture of wellness and prevention, says John Bluford, president and CEO of Truman Medical Centers, Kansas City, Mo., and the new chair-elect of the American Hospital Association.
Health care service is a family affair for me. I had many uncles in health care and my grandfather was a dentist. I went to Fisk University in Nashville majoring in pre-med and I was on my way to Meharry Medical School when a recruiter for Northwestern University's business program interviewed me. The gentleman tried to convince me that I ought to go into business because of my orientation toward extracurricular activities and leadership roles with my fraternity, student government and the basketball team at Fisk. I told him I knew nothing about business administration, but I passed the graduate school test and received a full two-year scholarship at Northwestern sponsored by what was then the United Insurance Company in Chicago, plus a $250 monthly stipend. In 1971, that was good spending money. So I enrolled in the business school with a hospital and health services major. The real hook was when I realized that you don't have to be a doctor to work in a hospital. You can lead a variety of activities that help support many doctors and their patients in an administrative role.
My first job in graduate school was at the 3,000-bed Cook County Hospital. As an administrative resident, I was the weekend administrator under Bill Silverman and Bob Shakno, both of whom came from Michael Reese Medical Center to help turn around Cook County Hospital in the early '70s. This was a very turbulent time at that county hospital, following much-publicized strikes by residents and nurses. After graduating from Northwestern, I took over as the night administrator. It was training under fire, but the beauty of it for me was that on weekends and nights, I had overall administrative responsibility for the hospital.
I have many stories after being the night administrator at Cook County. My favorite is the night I was looking at the surveillance television monitor and saw one of our buildings on fire. About 16 buildings comprised the Cook County campus and the psych hospital was on fire. I had Bob Shakno's home phone number. He always said, "If there are any problems, just call me." Well tonight was the night. His response: "Step No. 1: Call the fire department."
Today's Non-System
The business we're in today is very complex and often contradictory. We're rewarded for sickness but not wellness and prevention. So many component parts create this non-system—insurers, physicians, hospitals, pharma, device manufacturers—and each component part represents a competing interest that resists change. The cost of health care is a big issue and we all want to reduce cost. But someone's cost is someone else's revenue. Therein lies the root of many of the health care reform political battles inherent in moving the system forward. That is why I am so pleased with AHA's Health for Life platform (coverage, wellness, efficiency, highest quality and best information) as it takes a comprehensive look at the total system(s) for reform.
Today, many uninsured people lack access to appropriate care, at the appropriate time and the appropriate place. One way of thinking is that sick people don't need insurance; what they need is appropriate access to health care. Today, they often access health care through safety-net hospitals and emergency departments, where ongoing continuity of care may suffer. Appropriate health care reform, which increases appropriate access to services, may not be cheaper in the short run, but we might have a healthier society and other benefits to the common good.
The long-term key to success is the prevention of illness and managing the costs associated with sickness. A rallying cry around the country in support of lifestyle enhancement, physical fitness and good nutrition would be the biggest enhancement to health care reform that we could achieve from a quality-of-life perspective.
End-of-life care counseling can also have long-term results. Evidence already exists that a 90-year-old with multiple system failure can either stay in a highly intensified, technological ICU environment and have dozens, if not hundreds, of tests done by high-profile professionals for weeks or that person can go home and be treated with dignity and surrounded by loved ones. The irony is that the length of life is the same in either situation. But the choice for quality of life is a no-brainer. We are often incentivized to do more expensive yet less effective modalities. Unfortunately, end-of-life care issues were avoided in the current reform legislation, but eventually the collective American community must discuss it.
Societal Disparities
My 30-plus years in health care have been in the public or safety-net hospital environments that, on the whole, cater to a vulnerable patient population with a high degree of health care disparity. Their condition often represents social disparities—not just health care disparities. Ethnic and racial disparities come into play as well; but broadly speaking it encompasses the people with fewer employment opportunities, sometimes with poor family support, inadequate housing, and this aggregate population crosses all racial and ethnic boundaries. Much of the reform debate in terms of access and cost is really about this vulnerable patient population. If we focused our attention here and society provided resources to solve the underlying problems, we could carry health care reform further than any legislation.
The focus on continuity of care, medical home experiments and advocacy issues play neatly into helping us get our arms around the problem. Many of our clientele have chronic diseases that are not managed well, and they don't have system navigators to get patients from point A to point B to make sure they keep their appointments, manage medications, and so on. And in many cases, the people who treat them can't associate or identify with them to the extent that it takes to overcome or break through the social disparity aspects of their lives.
Research comes into play, but so does common sense. I get frustrated with "process" versus common sense and the prompt execution of good ideas. There sometimes needs to be a greater sense of urgency and balance between research, process and action. If we know that asthma is a problem for a pediatric patient who repeatedly comes to the emergency room, then someone needs to go to the home and find out what's going on in that environment that is creating the problem.
We are about to start a program at Truman Medical Centers that we call Passport to Wellness, which is targeted at our "frequent flyers"—those people who are constantly readmitted, who make a dozen or more visits a month to our emergency room, and have chronic diseases such as diabetes, hypertension, asthma, chronic heart failure. We want to identify about 100 of these patients and provide as much intense case management attention as possible to see if we can solve their issues.
Sometimes we need to think about different types of interventions in dealing with vulnerable patient populations. I was talking with the head of our EMS system about Passport to Wellness and he said, "I see some of these patients 20 to 25 times a month. Many are diabetic and they need medications and some basic assessment. They call us because they know that if they come in by ambulance they will come through the emergency entrance and won't have to wait two or three hours in the waiting room." Bingo. Why not use these talented, skilled emergency medicine service workers? They are at the house, they can administer the medicine, and in many cases they know the patient better than the rest of the health care system. Perversely, we would lose Medicare payment for a full run to the hospital, but the economical, simple thing to do may be to let the EMS workers meet the needs of the patient on the spot.
The whole mental health sector needs to be brought into play as well. A great proportion of the vulnerable patient population has either mental health or addictive behavioral problems. Also, many people who are incarcerated should probably be in a mental health institution, as should many of our homeless. Our society has not opened our eyes to those realities yet.
All of the significant mental health, psychological-related issues and clinical issues associated with behavioral health are upon us. It is a slightly different business than running an acute care hospital. It is often not a money-making proposition. The capacity is woefully low. But it needs to be addressed.
Safety-net hospitals are critical to the communities they serve, not just because they tend to serve the vulnerable and disadvantaged population; safety nets are not merely for the downtrodden. Safety-net hospitals provide services such as Level 1 trauma units, high-risk neonatal units, burn units, oral health, and teaching and training programs that are vitally important to the entire community and may not be available in other parts of that community's delivery system.
They are also major business entities. We hire a lot of people. Safety nets pay lots of payroll tax and contribute significantly to the local economy through the acquisition of supplies, commodities, construction projects and so on. And because most safety-net hospitals are in the urban core, it is even more critical that they continue to be one of the major engines fueling that inner-city economy.
The maintenance and survival of these institutions is an economic issue as much as it is a health care issue.
Unintended Consequences
There is no question that there will be unintended consequences all over the map as the reform process runs its course over many years. It took more than a generation for us to get into our current circumstance in regards to cost, value and quality, and it is going to take some time for us to find our way out. Whatever happens with health care reform legislation today, it will be constantly modified over the next 10 years until we have a system that is more resourceful and meets more needs than the system does today, at a reasonable and affordable cost.
A theme in this year's discussions is that hospital environments with employed physicians, such as Mayo and the Cleveland Clinic, have better continuity of care, better results and run more efficiently and effectively. The physicians and the hospital are not working at cross purposes with cross incentives. In most institutions, the hospital and the physicians are legally independent organizations, but they are connected at the hip financially; one can't move successfully without the other. The new world order through health care reform with strong disease management, bundled payments and gainsharing arrangements should lead us in more unified alignment.
There are two things that create problems for chief executive officers. One is ineffective relationships with physicians and the other involves poor decisions or implementation of major IT projects. Today, the electronic health record is top of mind. And it will benefit the system, patients and clinicians, but it is not the silver bullet. Migrating from paper records to electronic documentation is very difficult and expensive. Without a thorough operational audit of user requirements and fixing the problems in the manual process before automating simply means that you get bad processes faster.
Another element that is critical to hospitals' long-term success is high-performance governance. Qualified trustees who are engaged and buy into the mission of the institution will advocate for that mission throughout the community at large. One of management's responsibilities with the board is not merely answering the questions that they ask as truthfully and honestly as you can but also, in some cases, showing them what questions to ask because often they don't know. That kind of openness and transparency in governance makes for a much stronger institution and across the nation will lead to a much stronger health care delivery system.
This article 1st appeared in the December 2009 issue of HHN Magazine.
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