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.
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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 [email protected] 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
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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: [email protected]
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.
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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.
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