Strategic Management in Organisations

Strategic Management in Organisations Order Description Portfolio. Robin Hood Case Based upon the tutorial session on this case and from your analysis of the Robin Hood case, prepare a Learning Portfolio of approximately 500 words (see assignment instructions for details on word limits, referencing and appendices). The tasks are to: 1. By relating to both the Strategic Drift Model (Johnson, Scholes and Whittington 2011.p158) and the EVR congruency model determine: a) Where on the strategic drift model is Robin Hood’s organisation at the close of the case? b) Which of the possible EVR scenarios best explains the closing situation facing Robin Hood? Briefly justify both your arguments. 2. In order to regain EVR congruency and to realise Robin’s vision, what new mission and strategic options should Robin Hood and his merry men follow from now on and outline the immediate steps that should now be taken? Answers to the Portfolio questions must be brief and in a concise executive summary format which demonstrates your learning’s on the topics selected. Answers should be referenced in terms of both supporting sources of contextual evidence/argument and to the related literature in terms of underpinning theory and concepts. Portfolio Page Limits is 500 words each plus an allowance for up to a further 4 pages of appendices to support your argument Appendix 1 Robin Hood  - Introductory Case Study Joseph Lampel, New York University (1991) It was in the spring of the second year of his insurrection against the High Sheriff of Nottingham that Robin Hood took a walk in Sherwood Forest.  As he walked he pondered the progress of the campaign, the disposition of his forces, the Sheriff's recent moves, and the options that confronted him. The revolt against the Sheriff had begun as a personal crusade.  It erupted out of Robin’s conflict with the Sheriff and his administration.  However, alone Robin Hood could do little.  He therefore sought allies, men with grievances and a deep sense of justice.  Later he welcomed all who came, asking few questions and demanding only willingness to serve.  Strength, he believed, lay in numbers. He spent the first year forging the group into a disciplined band, united in enmity against the Sheriff, and willing to live outside the law.  The band's organisation was simple.  Robin ruled supreme, making all important decisions.  He delegated specific tasks to his lieutenants.  Will Scarlet was in charge of intelligence and scouting.  His main job was to shadow the sheriff and.  His men always alert to their next move.  He also collected information on the travel plans of rich merchants and tax collectors.  Little John kept discipline among the men and saw to it that their archery was at the high peak that their profession demanded.  Scarlot took care of the finances, converting loot to cash, paying shares of the take, and finding suitable hiding places for the surplus.  Finally Much the Millers son had the difficult task of provisioning the ever increasing band of Merrymen. The increasing size of the band is a source of satisfaction for Robin, but also a source of concern.  The fame of his Merrymen was spreading, and new recruits poured in from every corner of England.   As the band grew larger, their small bivouac became a major encampment.  Between raids the men milled about, talking and playing games.  Vigilance was in decline and discipline becoming harder to enforce.  “Why”, Robin reflected, “I don't know half the men I run into these days. ” The growing band was also beginning to exceed the food capacity of the forest.  Game was becoming scarce, and supplies had to be obtained from outlying villages.  The cost of buying food was beginning to drain the bands financial reserves at the very moment when revenues were in decline.  Travellers, especially those with the most to lose, were now giving the forest a wide birth.  This was costly and inconvenient to them, but it was preferable to having all their goods confiscated. Robin believed that it was time for the Merrymen to change their policy of outright confiscation of goods to one of a fixed transit tax.  His Lieutenants strongly resisted this idea.  They were proud of the Merrymen’s famous motto “rob the rich to give to the poor. ” “The farmers and the townspeople,” they argued “are our most important allies. " "How can we tax them, and still hope for their help in our fight against the Sheriff?" Robin wondered how long the Merrymen could keep to the ways and methods of their early days.  The Sheriff was growing stronger and becoming better organised.  He now had the money and the men and was beginning to harass the band, probing for its weaknesses.  The tide of events was beginning to turn against the Merrymen.  Robin felt the campaign must be decisively concluded before the Sheriff had a chance to deliver a mortal blow.  “But how,” he wondered, "could this be done?" Robin had often entertained the possibility of killing the Sheriff, but the chances for this seemed increasingly remote.  Besides, killing the Sheriff might satisfy his personal thirst for revenge, but it would not improve the situation.  Robin had hoped that the perpetual state of unrest, and the Sheriff's failure to collect taxes, would lead to his removal from office.  Instead, the Sheriff used his political connections to obtain reinforcement.  He had powerful friends at court and was well regarded by the regent, Prince John. Prince John was vicious and volatile.  He was consumed by his unpopularity among the people, who wanted the imprisoned King Richard back.  He also lived in constant fear of the barons, who had first given him the regency but were now beginning to dispute his claim to the throne.  Several of these barons had set out to collect the ransom that would release King Richard the Lionheart from his jail in Austria.  Robin was invited to join the conspiracy in return for future amnesty.  It was a dangerous proposition.  Provincial banditry was one thing, court intrigue another.  Prince John had spies everywhere, and he was known for his vindictiveness.  If the conspirators' plan failed, the pursuit would be relentless and retributions swift. The sound of the supper horn startled Robin from his thoughts.  There was the smell of roasting venison in the air.  Nothing was resolved or settled.  Robin headed for camp promising himself that he would give these problems his utmost attention after tomorrow's raid. Free Online OCR Home OCR API Contact us Comments Free Online OCR Convert JPEG, PNG, GIF, BMP, TIFF, PDF, DjVu to Text Select pages from 1 to 7 Recognition language(s) (you can select multiple) Rotate image 0° CCW 90° 180° CW 90° Page layout analysis - split multi-column text into columns Page of 7 Download Copy to Clipboard Google Translate Bing Translator Paste Online Edit Online Journalovaaluatioriih Clinical Practice 3:33;:- InternationalJournal of Public Health Policy and Health Services Research I Journal of Evaluation in Clinical Practice ISSN 1365-2753 HIT or Miss: the application of health care information technology to managing uncertamty In cllmcal decnsnon making Vahé A. Kazandjian PhD MPH1 and Allison Lipitz-Snyderman PhD2 1President, Center for Performance Sciences, Elkridge, MD, USA, Adjunct Professor, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA, Director, Information Systems and Analysis, The Maryland Patient Safety Center, Elkridge, MD, USA 2Postdoctoral Fellow, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Keywords Abstract appropriateness of care, information technology, medical uncertainty, safety Objective To discuss the usefulness of health care information technology (HIT) in assist- ing care providers minimize uncertainty while simultaneously increasing efficiency of the Correspondence care PrOVided- Dr Vahé A. Kazandjian Study design An ongoing study of HIT, performance measurement (clinical and produc- Center for Performance Sciences tion efficiency) and their implications to the payment for care represents the design of this 6820 Deerpath Road study. Since 2006, all Maryland hospitals have embarked on a multi-faceted study of Elkridge MD 21075 performance measures and HIT adoption surveys, which will shape the health care payment USA model in Maryland, the last of the all-payor states, in 2011. E-maili Vkazandlian@mhaonline-Org Methods This paper focuses on the HIT component of the Maryland care payment initia- tive. While the payment model is still under review and discussion, ‘appropriateness’ of This paper was based on the findings Of a care has been discussed as an important dimension of measurement. Within this dimension, Swdy funded by a grant from the Maryland the ‘uncertainty’ concept has been identified as associated with variation in care practices. Health seerceS COST ReVleW commlSSlon Hence, the methods of this paper define how HIT can assist care providers in addressing the (HSCRCl for the per'Od 2006-2008 concept of uncertainty, and then provides findings from the first HIT survey in Maryland to infer the readiness of Maryland hospital in addressing uncertainty of care in part through Accepted for publication: 24 February 2010 the use of HIT. do“ OJ 1 1 “1.13652753201O_O1483_X Results Maryland hospitals show noteworthy variation in their adoption and use of HIT. Whlle computerlzed, electronlc patlent records are not commonly used among and across Maryland hospitals, many of the uses of HIT internally in each hospital could significantly assist in better communication about better practices to minimize uncertainty of care and enhance the efficiency of its production. Uncertainty in clinical decision making is likely inevitable and has technical (uncertainty regarding what to do), personal (uncertainty been considered a defining feature of the medical field [1,2]. Care regarding patients’ wishes) and conceptual (uncertainty regarding providers may be faced with uncertainty during the application of how to apply abstract concepts to concrete situations) [6]. HIT evidence to specific contexts [as defines the practice of evidence- may have significant implications for managing uncertainty in based medicine (EBM)] [3] or because of the absence of evidence each of these three domains [7]. to guide their decision making. Health care information technol- ogy (HIT) may have considerable implications for the manage- IT to promote EBM ment of uncertainty in clinical decision making, ultimately reducing resource waste and improving appropriateness of care Information technology promotes the practice of EBM by [1,2,4]. improving provider access to clinical evidence and supporting Health care information technology as a broad concept refers to the appropriate application of clinical evidence to a patient and the strategy, through electronic media and tools, to identify, store, context. Hence, EBM minimizes technical uncertainty defined as process, maintain and use data for enhancing performance, a provider’s lack of, or incomplete, knowledge in certain areas advancing knowledge and demonstrating outcomes [5]. This paper [8] of case management. Technical uncertainty is also salient for revisits Beresford’s model of clinical uncertainty which highlights providers in training [9] or in fields with wide variation uncertainties that infiltrate and influence clinical decision making: across patients (e.g. emergency medicine) [1]. Immediate access 1108 © 2010 Blackwell Publishing Ltd, Journal of Evaluation in Clinical Practice 17 (2011) 1108-1113 Download Google Translate Bing Translator Edit Online Journal of Evaluation in Clinical Practice ISSN 1365-2753 HIT or Miss: the application of health care information technology to managing uncertainty in clinical decision making jep_1483 1108..1113 Vahé A. Kazandjian PhD MPH1 and Allison Lipitz-Snyderman PhD2 1 President, Center for Performance Sciences, Elkridge, MD, USA, Adjunct Professor, The Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA, Director, Information Systems and Analysis, The Maryland Patient Safety Center, Elkridge, MD, USA 2 Postdoctoral Fellow, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Keywords appropriateness of care, information technology, medical uncertainty, safety Correspondence Dr Vahé A. Kazandjian Center for Performance Sciences 6820 Deerpath Road Elkridge MD 21075 USA E-mail: vkazandjian@mhaonline.org This paper was based on the findings of a study funded by a grant from the Maryland Health Services Cost Review Commission (HSCRC) for the period 2006–2008. Accepted for publication: 24 February 2010 doi:10.1111/j.1365-2753.2010.01483.x Abstract Objective To discuss the usefulness of health care information technology (HIT) in assisting care providers minimize uncertainty while simultaneously increasing efficiency of the care provided. Study design An ongoing study of HIT, performance measurement (clinical and production efficiency) and their implications to the payment for care represents the design of this study. Since 2006, all Maryland hospitals have embarked on a multi-faceted study of performance measures and HIT adoption surveys, which will shape the health care payment model in Maryland, the last of the all-payor states, in 2011. Methods This paper focuses on the HIT component of the Maryland care payment initiative. While the payment model is still under review and discussion, ‘appropriateness’ of care has been discussed as an important dimension of measurement. Within this dimension, the ‘uncertainty’ concept has been identified as associated with variation in care practices. Hence, the methods of this paper define how HIT can assist care providers in addressing the concept of uncertainty, and then provides findings from the first HIT survey in Maryland to infer the readiness of Maryland hospital in addressing uncertainty of care in part through the use of HIT. Results Maryland hospitals show noteworthy variation in their adoption and use of HIT. While computerized, electronic patient records are not commonly used among and across Maryland hospitals, many of the uses of HIT internally in each hospital could significantly assist in better communication about better practices to minimize uncertainty of care and enhance the efficiency of its production. Uncertainty in clinical decision making is likely inevitable and has been considered a defining feature of the medical field [1,2]. Care providers may be faced with uncertainty during the application of evidence to specific contexts [as defines the practice of evidencebased medicine (EBM)] [3] or because of the absence of evidence to guide their decision making. Health care information technology (HIT) may have considerable implications for the management of uncertainty in clinical decision making, ultimately reducing resource waste and improving appropriateness of care [1,2,4]. Health care information technology as a broad concept refers to the strategy, through electronic media and tools, to identify, store, process, maintain and use data for enhancing performance, advancing knowledge and demonstrating outcomes [5]. This paper revisits Beresford’s model of clinical uncertainty which highlights uncertainties that infiltrate and influence clinical decision making: 1108 technical (uncertainty regarding what to do), personal (uncertainty regarding patients’ wishes) and conceptual (uncertainty regarding how to apply abstract concepts to concrete situations) [6]. HIT may have significant implications for managing uncertainty in each of these three domains [7]. IT to promote EBM Information technology promotes the practice of EBM by improving provider access to clinical evidence and supporting the appropriate application of clinical evidence to a patient and context. Hence, EBM minimizes technical uncertainty defined as a provider’s lack of, or incomplete, knowledge in certain areas [8] of case management. Technical uncertainty is also salient for providers in training [9] or in fields with wide variation across patients (e.g. emergency medicine) [1]. Immediate access © 2010 Blackwell Publishing Ltd, Journal of Evaluation in Clinical Practice 17 (2011) 1108–1113 V.A. Kazandjian and A. Lipitz-Snyderman to evidence and/or practice guidelines via hand-held wireless devices or computers enables providers to retrieve timely information. Electronic decision-support tools help providers make care choices in-line with current evidence at critical decision points. Also, communication tools, such as hand-held wireless devices, can facilitate timely communication between providers [10–12]. A critical component of the practice of EBM is the appropriate application of the known evidence [13] which, in a patient-centred health care system, should accommodate patient wishes [14]. In that process, personal uncertainty may arise from the lack of a preexisting provider/patient relationship, patient incompetence or a patient’s inability to communicate. Alternatively, if a provider has a preexisting relationship with the patient, his/her own emotions may interfere with care choices [8]. Relevant documentation, particularly for end-of-life wishes, in an electronic format gives providers access to patients’ wishes, especially in situations requiring immediacy [15]. Application of the evidence may be marked by conceptual uncertainty as well, as it is often difficult to apply the evidence to the situation at hand since ‘Illness rarely presents as a textbook case’ [6]. In making decisions within uncertain circumstances, access to complete and accurate documentation of patient’s history is crucial to clinical decision making and to prevent waste and errors. Communication tools also improve interaction and knowledge exchange between providers, particularly during transitions of care; for example, medication reconciliation efforts depend on the interoperability of IT systems. Conceptual uncertainty also comes into play after the initial care decision is made in terms of the patient’s physiological reaction to the care approach [8]. Providers are often uncertain as to how a particular patient will respond to a given treatment, despite known population-based outcomes. Electronic patient monitoring, especially when available remotely, help providers respond to problem situations quickly and to make any necessary modifications to care plans. The application of evidence-based practices is increasingly accepted in health care [13]. Yet, commensurate attention may not be devoted to the environment within which these practices are carried out optimally, for example hospitals’ communication environment. Recent understanding of medical errors, even when variably defined, points to untimely, incomplete and even misguided information as tops on error-enablers list [16]. Rather than the information itself, often it is the way the information is gathered and communicated that enables errors. Information technology applications provide assistance in standardizing the collection of the data and their communication during the provision of care. The introduction of IT, however, when post hoc, requires the retooling of an existing hospital’s physical environment (software, hardware, computers, hand-held devices, phones, etc.) as well as the changing of long established habits among and across providers. The latter may be the hardest challenge, as changing clinical practice styles has shown variable success [17]. The introduction of IT, par contre, seems to gain gradual acceptance by pharmacists and nurses. Immediately after its introduction, an IT system seems to enhance the reliability and timeliness of medication dispensing and delivery by promoting clarity in the communication among providers during treatment phases [18]. © 2010 Blackwell Publishing Ltd Why HIT is an integral dimension of quality and care improvement Gaps in the evidence The second benefit of an IT system is the minimization of uncertainty when there is no evidence-based protocol for the management of a patient. In this case, which is still the dominant situation in health care, communication across care providers renders the case management more of a ‘system approach’ [19] than one where a doctor deals alone with the uncertainties. It can be argued that even when uncertainties exist, the feedback, second-opinion and guidance from peers would lessen the chance of errors, or at least promote a change in management based on observations of the intermediate outcomes during the care episode. The link therefore between evidence-based practices, communication among care providers and the management of uncertainty is crucial during the pursuit of quality and safety of care. Technical uncertainty, as mentioned at the outset, is a barrier to the consistent delivery of high quality care. The gaps in evidence can be narrowed through clinical and epidemiological research which are insufficiently conducted, as an estimated 80% of medical care lacks research evidence, resulting in wide variations in care [20]. Technical uncertainty may lead to missed opportunities or the overuse of medicine (e.g. superfluous tests and procedures), which translate into resource waste and potentially avoidable costs [8]. HIT has the potential to help close the evidence gap by facilitating research efforts through improved data availability. In particular, standardized electronic medical records may improve the quality and quantity of clinical data that can become available for research purposes and open new research possibilities [21]. Furthermore, comprehensive data sources created through electronic records would promote epidemiological research to help attribute clinical interventions on population health and changes in diseases. Evidence or reference? Knowledge will expand, diversify and specialize. Evidence will continue to be demanded for, not only by direct care providers but also by those evaluating the care [22] by cross-tabulating appropriateness of the care with its cost [23]. Realizing that evidence takes time to be established, it seems necessary to have alternatives to iron-clad evidence about ‘doing the right thing, to the right patients, at the right time, the right way, all the time’ [24]. It is proposed that when evidence is lacking, appropriateness can still be evaluated through the use of references. Specifically, a reference is a measurable type of extent of performance that allows a comparison with your own performance. Aspirin at admission or beta-blockers at discharge for acute myocardial infarction patients are the simplest of examples. To know if your performance is comparable with the mean, median, 10th percentile or to your professional peer group, indicator-based comparative data are desirable. These data, requiring a well-designed collection and dissemination infrastructure, require an IT structure in a hospital, and eventually across the continuum of care. These comparative data will not necessarily tell what is the right thing to do (it is theoretically possible that everyone else may be doing the wrong thing), but will provide timely, quantitative, trendable data leading to performance review. Figure 1 shows the relationship between knowledge and uncertainly as knowledge expands, diversifies and specializes over time. 1109 Why HIT is an integral dimension of quality and care improvement V.A. Kazandjian and A. Lipitz-Snyderman We know what we know Expansion of Knowledge We know what is being researched We know what works New level of knowledge Adapted from: GhoshAK. On the challenges of using evidence-based information: the role of clinical uncertainty. J Lab Clin Med. 2004 Aug;144(2):60-4. Beresford EB. Uncertainty and the shaping of medical decisions. Hastings Cent Rep. 1991 Jul-Aug;21(4):6-11 Figure 1 EBM, uncertainty and IT. EBM, evidence-based medicine; IT, information technology. Table 1 Direct and indirect uses of IT when dealing with uncertainty Direct Indirect IT crucial in: • Knowing what we know • Knowing what works When the levels of uncertainty increase with new knowledge, IT is needed to do comparative analysis, even if said analysis provides reference only and not evidence. For example, knowing if beta-blockers are prescribed and how often at discharge for acute myocardial infarction patients will raise the awareness of peers rather than explore if beta-blockers are the right thing to prescribe. This is where IT, EBM and comparative analysis via indicators minimize errors and enhance appropriateness. IT necessary in: • Establishing a communication infrastructure • Establishing evaluation of processes and outcomes of care Uncertainty can be ‘perpetuated’ if old knowledge is not challenged. Analytical work require data and systematic linkages across the domains of prevailing practices and recommended better practices. Without IT, the linkages between what is done, why and what impact it has had cannot be carried out on an ongoing basis. EBM, evidence-based medicine; IT, information technology. The boundaries of the knowledge are made of uncertainty, and evidence may not necessarily decrease uncertainty over time, although it may alter the types of uncertainty during the provision and receipt of health care. The use of references, when evidence is lacking, may provide timely and convincing guidance for care providers to review and evaluate the appropriateness of their performance. Over time, the understanding accumulated from appropriate care models may inch closer to enhancing the evidence-base of knowledge. The benefits of IT during the pursuit of appropriateness of care are summarized in Table 1. Technologies for uncertainty management: Maryland as a case example The state of Maryland conducted an assessment of the adoption levels of HIT across its hospitals as part of its ‘Quality-based 1110 Reimbursement Initiative’ (QBR), led by the Health Services Cost Review Commission (HSCRC). Within the context of this comparative performance initiative, IT has relevance for QBR in terms of data collection and analysis, as well as for managing clinical uncertainty more broadly. The HSCRC is a government agency with the authority to establish payment levels for both inpatient and outpatient services for all general acute care hospitals in the State. By law and consistent with the State’s unique Medicare waiver (Section 1814(b) of the Social Security Act), all payers must pay hospitals on the basis of the rates established by HSCRC. Since the inception of rate setting in 1974, HSCRC has used financial incentives to promote efficiency and achieve other goals of expanded access to care and payment equity. In 2004, the HSCRC considered a ‘Quality-based Reimbursement’ to adjust hospitals’ rates not only on utilization and efficiency but also on the basis of ‘quality’ [25]. A blueprint for action © 2010 Blackwell Publishing Ltd V.A. Kazandjian and A. Lipitz-Snyderman was developed and the QBR was launched in 2005. HSCRC contemplated some type of infrastructure support as part of its overall strategy of improving the quality of Maryland hospitals’ care, and HIT received special attention. The HSCRC authorized the funding of a statewide survey of HIT used in Maryland hospitals as well as the documenting of the needs for HIT, by type, recognized by the hospitals. This statewide assessment has broad relevance for uncertainty management in clinical decision making through its focus on Maryland’s use of IT for quality improvement and administrative purposes as well as its capacity for electronic data collection to support comparative analysis efforts including the QBR. A follow-up survey is currently underway which will offer insights into how technology adoption has changed over time. The first survey and analysis were carried out over 18 months by the Maryland Patient Safety Center (http://www.maryland patientsafety.org) in 2006. The survey tool incorporated fieldtested types of questions about the organizational needs for HIT by type, the hospitals’ readiness to use these HIT and specific details about how HIT are currently being used in each hospital. Overall, the frequencies reported for use of specific technologies in Maryland were largely consistent with national estimates [26–29] and varied widely by type of technology and by hospital. Adoption frequencies of some of the technologies related to uncertainty management are included in Appendix 1. In general, there is gradient variation between hospitals rather than an observed ‘all or none’ hospital pattern of technology adoption. Frequencies for most of the technologies included in the assessment are on the low side, and even those technologies with high frequencies do not reach 100% adoption across Maryland hospitals. Therefore, the 34 hospitals responding hospitals confirmed that there is much room to (1) improve the frequency of technology adoption; and (2) bring hospitals closer to each other in the adoption and implementation of specific technologies. While leading hospitals do set an example and show how IT can improve performance [11], diverse statewide strategies may be used to enhance quality and safety of care for all hospitals, by increasing availability of and access to evidence, information and resources, as well as by facilitating comparative analysis through the use of references. Conclusion This paper proposes that when IT is discussed within the context of enhancing appropriateness of care, the influence of uncertainty on existing evidence for appropriate care should be considered. While there is literature on the role of uncertainty in the application of medical knowledge, the suggestions of this paper go beyond the conundrum of uncertainty and incomplete availability of evidence to propose that IT can facilitate appropriate medical care and support performance improvement through comparative analysis. Specifically, references, rather than evidence, are used during comparative analysis to trigger the evaluation of performance. Such organizational introspection is also expected to lead to extrospection where individuals or hospitals identify better performers and try to learn not only about better processes but the linkages of these processes to outcomes. © 2010 Blackwell Publishing Ltd Why HIT is an integral dimension of quality and care improvement Acknowledgements The authors thank Mr Robert Murray, Executive Director of Maryland’s HSCRC for his continuous support of academic work based on the HSCRC initiatives. We would also thank the Maryland Patient Safety Center (MPSC) for making academic manuscript preparation part of its strategy for communication about better safety practices and evaluation of their impact. References 1. Timmermans, S. & Angell, A. (2001) Evidence-based medicine, clinical uncertainty, and learning to doctor. 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Appendix 1 Examples of adoption frequencies of information technologies related to uncertainty management Potential uncertainty domain addressed Technology Q1. Handheld wireless devices Physician use At least some use 81–100% of physicians Nurse use At least some use 81–100% of nurses Q2. Physicians ability to access the following functions from the hospital Medical image review EMR Online formulary Clinical guidelines/pathways Patient scheduling Electronically generate prescriptions Send prescriptions to pharmacy electronically Q3. Physician access to clinical guidelines/pathways performed via mobile/wireless device Q4. Physician access to information online Patient demographics Results review – lab Medical history Clinical alerts Observations, orders and progress notes Results review – consultant report Nurses’ notes Report review – medical image Clinical guidelines/pathways Medical image review Q5. Alerts utilized online in real-time by physicians Allergy alerts Organization-specific general rules Drug-drug interaction alerts 1112 Frequency of adoption T (Technological) P (Patient) C (Conceptual) T P C T P C P C C 68% of hospitals 24% of hospitals 47% of hospitals 21% of hospitals Question average: 49.3% 68% of hospitals 68% of hospitals 65% of hospitals 47% of hospitals 44% of hospitals 35% of hospitals 18% of hospitals Hospital average: 2.4% of physicians Question average: 52.6% Hospital average: 82% of physicians Hospital average: 73% of physicians Hospital average: 66% of physicians Hospital average: 63% of physicians Hospital average: 55% of physicians Hospital average: 53% of physicians Hospital average: 50% of physicians Hospital average: 33% of physicians Hospital average: 30% of physicians Hospital average: 21% of physicians Question average: 17.5% Hospital average: 29% of physicians Hospital average: 23% of physicians Hospital average: 22% of physicians T T C C C T T C C C C T C C C C T T C C C T C © 2010 Blackwell Publishing Ltd V.A. Kazandjian and A. Lipitz-Snyderman Why HIT is an integral dimension of quality and care improvement Appendix 1 Continued Potential uncertainty domain addressed Technology Frequency of adoption T (Technological) Dose checking (max/min) Duplicate order alerts Test prep alerts/guidelines Dose suggesting Drug-diet checking Therapeutic overlap alerts Test sequencing alerts/guidance Q6. Electronic data for medical record available from other systems digitally (at least some availability) Q7. CMS quality indicator data electronically extracted from EHR/EMR and entered into electronic file without human intervention (at least some data) Q8. Maryland Quality Indicator Project data electronically extracted from EHR/EMR and entered into electronic file without human intervention (at least some data) Q9. Equipment that feeds readings directly into the medical record using online technology (pilot program or fully deployed) Blood glucose Bedside vital signs Fetal monitor EKG Ventilator Cardiovascular functions IV pump Intracranial monitor Q10. Providers can access data through a computer Lab data Radiology reports Pathology data Radiology images Cardiology data Pulmonary data Q11. Electronic documentation of nursing care (more than 75% of documentation is electronic) Q12. Alert system tied to patient monitoring surveillance system Any alert system For critical care units For step down units For general med/surg units Q13. Organization provides digital clinical imaging to the following appropriate care provider in hospital setting Radiology Nuclear medicine Cardiology Neurology Oncology Pathology Hospital average: Hospital average: Hospital average: Hospital average: Hospital average: Hospital average: Hospital average: 83% of hospitals T 20% of physicians 20% of physicians 16% of physicians 13% of physicians 13% of physicians 11% of physicians 8% of physicians P (Patient) C (Conceptual) C T T T T T C P 24% of hospitals T 15% of hospitals T C Question average: 22.9% C 50% of hospitals 26% of hospitals 26% of hospitals 24% of hospitals 21% of hospitals 18% of hospitals 12% of hospitals 6% of hospitals Question average: 74.5% 91% of hospitals 88% of hospitals 79% of hospitals 71% of hospitals 65% of hospitals 53% of hospitals 38% of hospitals C C C C C C C C C C C C C C C C 44% of hospitals 38% of hospitals 15% of hospitals 9% of hospitals Question average: 36.8% C C C C C 76% 59% 35% 21% 18% 12% C C C C C C of of of of of of hospitals hospitals hospitals hospitals hospitals hospitals Notes: This table includes a selection of technologies included as part of a Maryland assessment of information technology adoption. The findings are based on data from 34 Maryland acute hospitals, representing, on average, more than 2300 employees. A total of 44 questions were included in the summary analysis. ‘Question averages’ were calculated by averaging all question sub-parts. PLACE THIS ORDER OR A SIMILAR ORDER WITH US TODAY AND GET AN AMAZING DISCOUNT :)