Another tactic of the Wellness-Plus Solution is the development and use evolving software tools to collect, share, analyze and discuss data and information to help improve care quality and prevent illness by helping stakeholders build and use evolving clinical knowledgebases.

This tactic requires next-generation health information technology (HIT) system that enables everyone to:
  • Understand each patient’s health problems and needs in fine, clear detail, to support accurate diagnostic and treatment prescription decisions
  • Know the safest and most cost-effective ways to care for each patient and help implement that care properly across the entire healthcare continuum
  • Know how to prevent illness and promote wellness for each person
  • Deliver care in a coordinated manner and with minimal error and omissions
  • Understand the outcomes of treatment interventions and wellness programs
  • Protect populations in the event of a wide-spread emergency (e.g., bioterrorism, epidemic)

HIT holds great promise for delivering the right information at the right time to the right people, and for supporting processes that promotes safe, effective, and more affordable care through adherence to evidenced-based practice guidelines, monitoring and surveillance, medication error reduction, and decreased rates of redundant or inappropriate care.[1,2,3]

To accomplish this, a flexible, efficient, interoperable information system must be deployed, which accommodates any current and future data and operational standards. It must have of a variety of advanced HIT tools incorporated into a highly-secure, economical, easy-to-use, always available, point-of-care software system that:
  • Collects and integrates a lifetime of patient data across all areas of care to generate a deep, detailed picture of each patient and the care rendered
  • Enables the fluid exchange of the data wherever and whenever it is needed, and presents the data in ways tailored to each stakeholders needs
  • Helps clinicians make and justify diagnostic and treatment determinations
  • Helps clinicians establish plans of care by recommending appropriate practice guidelines tailored to the needs of each patient and healthcare disciplines/specialties
  • Helps collaborative networks of providers, researchers, and knowledge management specialists analyze, discuss, and interpret care process and outcomes data to build evolving knowledgebases of evidence-based diagnostic and practice guidelines for continuous improvement of care quality
  • Enables consumers, purchasers and payers to get information they need to support their decisions
  • Provides alerts and reminders to help prevent errors and omissions
  • Manages plan of care execution to assure orders are carried out with minimal disruption
  • Coordinates care across the entire healthcare continuum
  • Speeds workflows by streamlining tasks, such as scheduling, ordering, data entry, and generating forms and reports
  • Performs continuous biosurveillance and crisis management functions to help first responders, hospitals, and public health agencies handle emergencies, as well as post-market drug and medical device surveillance to identify dangerous medications and equipment
  • Support communications and discussions among loosely connected groups of individuals.

Decision Support Capabilities

Computerized clinical decision support (CDS) tools ought to have the following characteristics:
  • Speed. When a clinical decision support system is slow, for whatever the reason, user satisfaction declines markedly. Taking more than a second or two to move from one screen to another is unacceptable to most clinicians.
  • Anticipate needs and deliver in real time. The information a provider needs not only has to be available, but applications should anticipate what clinicians need and deliver that information when they need it, whether they are consciously aware they need it or not. Recommending a clinician change drug dosage or use different procedures based on patient condition is an example of this.
  • Fit into workflows. Clinicians are more likely to use guidelines when the information is presented in during the natural course of work. Presenting a guideline involving medication as the clinician is ordering exemplifies this process.
  • System design through end user feedback. Developers should do substantial usability testing to obtain user feedback and guidance in order to make sure the software is easy to operate, effectively alerts clinicians when their immediate attention is necessary, has screens and controls that are not confusing, etc.
  • Flexible and complete. The system should enable clinicians to override suggestions and reminders, avoid redundancies, and offer alternatives when available.
  • Uses one screen. Having a guideline fit on a single screen works best.
  • Minimizes requests for additional information. Do not require the clinician to input more data than is necessary. For example, access required patient data automatically from a database when possible.
  • Evaluates outcomes. Determine how effective care is when implementing a guideline and adjust the guideline accordingly.
  • Evaluates compliance and variance. Determine the rate of compliance to a guideline and the reasons for variance from the recommended procedures, adjust the guideline accordingly.
  • Has an adequate degree of computer automation. There is a range of guideline automation; (1) The computer offers no assistance; humans must do it all, (2) The computer offers a complete set of action alternatives, and (3) narrows the selection down to a few, (4) suggests one, and (5) executes that selection if the human approves, or (6) allows the human a restricted time to veto before automatic execution, or (7) executes automatically, then necessarily informs the human, or (8) informs him or her after execution only if he or she asks, or (9) informs him or her after execution only if it, the computer, decides to. (10) The computer decides everything and acts autonomously, ignoring the human.[4]
  • Patient specific. The system should “provide access to information relevant to the specific patient in the context of the current situation and in relation to the whole patient and his or her predispositions. … Once the information is collected, refined, and distilled, an intelligent engine can sift through the aggregate to identify patterns and test for statistical relevance. The intelligent engine will compare the specific attributes of the patient (gender, age, family history, conditions, vital signs, etc.) to find success factors common with the aggregate pool of similar patients. The power of pattern recognition over the aggregate, but applied to the specific patient, yields personalized medicine. Personalized information is more likely to result in positive outcomes and to stimulate a positive change in the patient's behavior.”[5]

Much still needs to be done before decision support software reaches anywhere near its potential. An effective CDS “provides clinicians, staff, patients or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care. It encompasses a variety of tools and interventions such as computerized alerts and reminders, clinical guidelines, order sets, patient data reports and dashboards, documentation templates, diagnostic support, and clinical workflow tools. CDS has been effective in improving outcomes at some health care institutions and practice sites by making needed medical knowledge readily available to knowledge users. Yet at many other sites, CDS has been problematic, stalled in the planning stages, or never even attempted. As a result, relevant medical knowledge that should be brought to bear is not always available or used for many health care decisions in this country. This is an important contributor to the well documented problems and sub-optimal performance of our health care system. Further, growing consumerism throughout U.S. society, along with efforts to shift the costs of care to patients and expand patient participation in health care decisions, are driving increasing patient and consumer demand for access to reliable medical information. Achieving desirable levels of patient safety, care quality, patient centeredness, and cost-effectiveness requires that the health system optimize its performance through consistent, systematic, and comprehensive application of available health-related knowledge – that is, through appropriate use of CDS.[6]

Types of Software Tools Needed

Following is a description of key software tools in use today, as well as new categories of tools being developed. Unfortunately, the definitions of these tools are often blurred, as one category mixes with others. In this paper, therefore, an attempt is made to clarify the definitions using these tool function categories:
  • Information integration and exchange (including record-sharing and other communications)
  • Information input, storage, and access
  • Decision support (clinical decision support involves diagnostic, treatment prescription, treatment execution and alerting, and treatment coordination decisions; there is also business decision support)
  • Treatment process and outcome evaluation
  • Knowledge development (including knowledge management, research support, business intelligence, provider and consumer education)
  • Collaboration support (virtual forums and collaborative spaces).

Computerized Health Agents (CHAs)

Functional categories: (a) Information integration and exchange; (b) Information input, storage, and access; (c) collaboration support.

The ideal HIT system would enable stakeholders to access all information, software tools, and people in one place, through a single gateway, with a single user account and sign-on. Instead of requiring expensive and difficult to manage grand-scale centralization or use of unique patient identifiers, patient data would be stored in many separate databases located in each provider’s office or facility, in decentralized “silos” as they are now, and a “Record Locator Service” is used to enable data exchange, which is something that has already been successfully demonstrated.[7]

In addition, the data would be shared by transporting it easily, securely, quickly, and inexpensively, without having to contend with firewalls. It would handle any data type and formats, and would perform any necessary transformation to enable data to move between divergent sources.

The system would able to access web sites as well as desktop applications. It would work for people who are connected to the internet only occasionally and in low bandwidth environments, so it doesn’t require constant online connectivity or broadband. Any number of people would be able to use the system at the same time (unlimited “scalability”) with no noticeable slowdown. Stakeholders would receive only the data for which they are authorized, presented in a way that is useful and meaningful to each of them, and patients control what personal data others can see. The system would be able to use the tools and databases of any HIT vendors (i.e., be “interoperable”). And the system would allow people to connect and collaborative with on another in flexible peer-to-peer (P2P) node networks.

These requirements can be accomplished using computerized health aents (CHAs), which are nodes (software programs) for connecting people-to-people and computers-to-computers via publisher-subscriber based P2P networks. They use configurable templates for data analytics, transformation, and reporting; and it uses e-mail to distribute very small, virus-proof, highly secure text files containing patient and treatment data.[8]

Diagnostic Aids

Functional categories: Decision support diagnostics; and may be combined with other tools for treatment prescription decision support.

Diagnostic aids software applications were discussed earlier. Some enable patients to input data about their health problem at home or in the clinician’s office, while others collect data from the provider only. Some use the Web and others do not, and some use both.

These tools can help improve care quality by suggesting diagnoses, some of which clinicians may not have considered. This has shown to be especially useful patients suffering complex or unusual problems.[9]

In the ideal HIT system, the diagnostic aid would be integrated with other tools discussed below to assist in the selection of evidence-based interventions and evaluation of outcomes. For example, it could perform a triage assessment prior to visiting a primary care physician’s office to help determine whether the patient must be seen, how the appointment should be, who should see the patient, how much time to allow for the visit, and whether any testing should be done prior to the visit. During the office visit, data from patient’s physical examination, medical history, and laboratory results would be analyzed to give the physician lists of diagnostic and treatment options to consider, along with the pros and cons of different interventions and access to research materials supporting them, as well as suggestions for additional investigational studies to confirm the presence of a given diagnosis.

This tool would be used routinely to assess all patient problems, not just for consultation of difficult cases, since problems that appear simple are actually found to complex, and because it is too easy for a clinician in a busy office to forget to ask important diagnostic questions.[10]

Diagnostic aids can also be used as a teaching tool with consumers, a way to empower consumers with a list of assessment findings to share with their healthcare provider that facilitates dialogue about treatment options and self-care strategies.[11]

Electronic Health Record (EHR)

Functional categories: Information input, storage, and access; and may be combined with other tools for treatment prescription decision support.

An electronic health record (EHR) – which may also be called an electronic medial record (EMR), electronic patient record (EPR), computerized patient record (CPR), as well as other names – is a patient record system for managing clinical information and making it available to clinicians for better delivery of care. They may be limited in their scope to a single area of clinical information (such as laboratory data) or designed for a specific healthcare specialty, or they may be very broad in scope and multidisciplinary.

While some definition of EHR include the functions of computerized physician order entry and decision-support software tools (discussed later), these other tools are put into their own categories in this paper. Nevertheless, these tools typically work with EHRs and some are actually built into certain EHR products.

The ideal EHR would work in conjunction with other HIT tools to help improve care healthcare quality by:
  • Enabling all providers participating in a patient’s care — across all specialties and settings — to access and discuss essential clinical data[1] quickly, easily, and securely, anywhere and anytime, which are presented in ways tailored to each provider’s needs
  • Collecting and storing a lifetime of detailed patient information, which would be used to track patients’ health over time, including presentation of graphs showing, for example, changes in diabetic patients’ glucose and cholesterol levels with indications of unacceptable readings
  • Sending certain data automatically to researchers stripped of patient identifiers for quality improvement studies, as well as for biosurveillance and after market drug surveillance.
  • Helping eliminate error, inconsistencies, omissions using alerts, warnings, and reminders
  • Incorporating data from diagnostic decision aids into a patient’s record
  • Working with computerized decision-support systems, such as practice guidelines and clinical pathways (discussed below) to help improve decision making and care delivery
  • Working with computerized physician order entry (CPOE) systems (discussed below) to streamline the entry and storage of orders for prescriptions, tests, and ancillary services
  • Being incorporated with personal health records (discussed below)
  • Including computerized administrative tools, such as scheduling systems
  • Maintaining a data trail that can be readily analyzed for medical audit, research and quality assurance, epidemiological monitoring, etc.
  • Generating reports accommodating federal, state, and private reporting requirements, such as patient safety and disease surveillance reports.
  • Providing high-level security, including alarms for breaches, secured access by authenticated users only, authorization access to the system with fine-grained permissions, audit logs tracking all activity, automatic termination of abandoned sessions (time-outs), strong encryption based on secure sockets layer
  • Providing data validation to make sure they are accurate and complete
  • Providing inter-office communications, so staff can communicate with one another by, for example, using internal e-mail
  • Being flexible enough to accommodate current and any future data format and delivery standards
  • Saving time and work through elimination of redundant data entry, voice dictation (recognition and transcription), patient letters templates, electronic signatures, automating certain administrative requirements
  • Enabling paper records to be scanned into the system
  • Managing transcription reports and progress notes.[15,16,17]

There are many different EHRs on the market. Some are for hospitals and clinics, and some for solo and group practices. Studies in ambulatory care settings estimate that EHRs would help save $112 billion per year.[18]
Advice to providers using EHRs for patient-centric care, include:
  • Use a mobile monitor, such as a flat screen on a movable arm, a tablet PC, or a laptop
  • Push the computer screen away and focus on the patient
  • Inform patients about what you are doing as you are doing it.
  • Encourage patients to participate in the process.
  • If possible, have staff handle routine data entry either before or after a patient encounter.[19]

Links to blogs:
» A physician describes his experiences with and recommendations for implementing EMR
» Vendors must understand the needs of the small practice office
» Using EMR for diabetes care

Personal Health Record (PHR)

A Personal Health Record (PHR), unlike the EHR, focuses on the information needs of the patient/consumer. An ideal PHR would:
  • Give patients easy access to their health records
  • Offer a convenient way for patients to enter information into their EHR for use by their providers, or to another care giver in case of an emergency
  • Enable patients to authorize and restrict access to particular practitioners for specific pieces of information in their EHR
  • Provide interactive patient education to help them better understand medical conditions and medications
  • Help them carry out home-monitoring and self-testing can improve control of chronic conditions, such as such as cholesterol results and blood pressure readings.

A majority of people interviewed would use a PHR. Those with greater health care needs expressed the highest interest: 65 percent of people with chronic illness say they would use one, while 58 percent of those without chronic illness reported they would.[20]

Computerized Physician Order Entry (CPOE) Tools

Functional categories: Information input, storage, and access; and may be combined with other tools for treatment prescription decision support.

Computerized physician order entry (CPOE) tools streamline the entry and storage of orders for prescriptions, tests, and ancillary services. They typically work in conjunction with EHRs and incorporate decision support capabilities. CPOEs are designed to enhance legibility, reduce duplication, and improve the speed with which orders are executed. In addition to electronic prescribing, they may include electronic referrals radiology and laboratory ordering and results display, the ability to track order execution, and offer support for continuing medical education.

Their decision support functions help improve care quality by reducing errors. For example, CPOEs may include a menu of medications with default doses and a range of potential doses for each medication. They may check for drug-allergy contradictions and drug-drug interactions, do drug-laboratory value checks, and display a patient’s relevant laboratory results on the screen at the time of ordering. They may warn the physician about possible adverse drug interactions and improper dosages. In addition to providing reminders about corollary orders (e.g., prompting the physician to order glucose checks after ordering insulin), and they may display drug guidelines as the order is being made.

Research studies supports for CPOE's beneficial effect in reducing medication errors caused during the processes of ordering, transcribing, dispensing, administering, or monitoring medications.[21] Other research has demonstrated impressive reductions in adverse drug event costs when a CPOE system with decision support capabilities is used, such as prescribing cheaper but equally effective drugs, reducing unnecessary lab tests, and using evidence-based treatment guidelines.[22] It is estimated that use of CPOEs can reduce adverse drug event by 2 million annually, 130,000 of which are life-threatening; will save approximately $44 billion with nationwide each year; eliminate more than $10 in rejected claims per outpatient visit, totaling more than $9 billion per year. [23]

Note, however, that there is room for improvement as evidenced by a recent study in one hospital that found CPOEs could actually lead to errors in almost two dozen situations. While there is still strong agreement that CPOEs will prove their value in reducing errors and healthcare expenses, this shows the need for early testing of HIT products and their ongoing refinement and improvement.[24]

Evidenced-Based Computerized Practice Guidelines and Clinical Pathways with Advanced Capabilities

Functional categories: decision support - treatment prescription and execution; may also include (a) Information input, storage, and access; (b) treatment process and outcome evaluation; and (c) knowledge development.

Computerized practice guidelines, treatment planners, and clinical pathways help providers deliver care by recommending and tracking specific interventions based on certain patient diagnoses. Some of these tools have sophisticated decision-support capabilities, evaluate treatment process compliance and outcomes, and possess knowledge development capabilities, while others do not. And they need not be evidence-based.

The Quality though Knowledge model, however, focuses on using tools with these capabilities, even if few such advanced tools exist today. These advanced tools help guide the execution of interventions by presenting a patient’s plan of care, track clinicians’ actions, evaluate the outcomes, and promote knowledge growth.

Computerized Practice Guidelines

Evidence-based practice guidelines were discussed in detail earlier in this paper. They help improve healthcare quality by describing explicit and well-defined standards of care for specific health problems based on scientific research. Software programs that presents such guidelines — using different rules (algorithms) to determine which evidence-based interventions to recommend — are called computerized practice (or clinical) guidelines.

Different types of computerized practice guideline tools employ different techniques to decide the particular interventions to recommend based on a patient’s condition and characteristics.[25]

Evidence-based computerized guidelines have benefits paper-based guidelines do not, including:
  • Using a patient’s diagnostic and demographic data, they automatically select the most appropriate guidelines for the provider’s consideration
  • Offering ready access to reference materials providing access to information about evidence-based research supporting a guideline, as well as instructional information to providers for delivering the recommended interventions and to patients for self-management of their care
  • Helping clarify a guideline by, for example, specifying decision criteria and clinical recommendations
  • Using reminders, prompts, and alerts to improve compliance with preferred clinical practices
  • Helping patients communicate, work cooperatively, and participate actively with clinicians.[26]

In addition, computerized guidelines having advanced capabilities help improve care quality by evaluating treatment processes and outcomes and developing clinical knowledge through the:
  • Access to and analysis of variance data, which indicates the degree of compliance with the guidelines and reasons for non-compliance
  • Access to and analysis of clinical and financial outcomes data, which helps determine the safety and cost-effectiveness of care implemented in accordance with and at variance from a guideline’s recommended interventions
  • Improvement of multidisciplinary communication, teamwork, and care planning by enabling the variance and outcomes data, as well as the guidelines criteria and rules, to be shared and discussed among collaborative teams
  • Improvement of patient care documentation
  • Support of provider training and patient awareness through the delivery of educational materials
  • Continuous auditing of clinical practice to provide valuable feedback to the provider.

Ideally, practice guidelines should be specific to the individual patient and not simply give recommendations based on heterogeneous groups of patients, which fail to consider the particular needs and circumstances of the particular patient. This is only possible through ongoing collection and analysis of outcomes data, and use of that data to fine tune guidelines to account for patient a wide range of patient differences.

Clinical Pathways

Evidenced-based clinical pathways (also called critical pathways, care pathways, integrated care pathways, multidisciplinary pathways of care, pathways of care, care maps, collaborative care pathways), which were introduced in the US and UK in the early 1990s, are similar to computerized practice guidelines in that they both present practice guidelines via software programs.

There are distinct differences, however. Computerized practice guidelines are used for ambulatory/outpatient care, so the recommended interventions are not presented on a day-by-day basis. Instead, if a patient’s treatment is rendered over multiple visits, a computerized practice guideline may suggest diagnostic assessments in the initial visits, then offer treatment intervention recommendations based on the assessment, and follow-up procedures if necessary.

A clinical pathway, on the other hand, transforms a practice guideline into a series of interventions spanning multiple days of care for hospitalized patient in hospitals and multidisciplinary teams focused on providing coordinated care.In clinical pathways, care events are mapped on a timeline or series of tasks including tests/assessments, treatments/procedures, medications, consultations, diet, teaching (including patient education), and preparing for discharge or transfer.[27,28,29]

Basic clinical pathways have four main components: a timeline, the categories of care or activities and their interventions to use, intermediate and long term outcome criteria, and the variance record, which documents deviations for analysis).[30]

The most advanced clinical pathways tools evaluate treatment processes, patient progress, and outcomes, which help develop clinical knowledge as they improve care quality by offering these capabilities:
  • Expert systems to help determine an initial diagnosis and treatment regimen, provide daily assessments of the patient's condition and make subsequent adjusts the regimen as necessary
  • Accesses and processes outcome data, including patients' clinical condition at discharge/termination, length of stay, expenditures, unplanned readmission rates, and satisfaction levels
  • Identifies why each process variance occurred, e.g., as a result of patient, provider, internal system, and/or external system factors)
  • Shows how the variance relates to outcome measures; that is, how deviations from the pathway affect patients' health, functionality, length of stay, expenditures, readmission rates, and satisfaction levels
  • Specifies the nature of variance, including whether each variant process was done late, early, or not at all, or if new processes were added to the pathway at time of care.

With this information, additional knowledge is gained. For example, if compliance with a particular pathway results in positive outcomes with particular patient, the pathway receives validation support; if it doesn’t; knowledge is gained about how the pathway may best be modified (e.g., it may show that when medication X is administered to patients with diagnosis Y earlier in the pathway than originally recommended, the outcomes are significantly better). This information also identifies why particular pathways are not followed precisely, so that action can be taken to enhance compliance to pathways that bring about positive outcomes.[31]

As with practice guidelines, clinical pathways should be specific to the particular needs and circumstances of the particular patient.

Links to blogs:
» Technology Support for Evidence-based Medicine

Care Plan Coordination Tools

Functional category: Treatment coordination decision support

Care Plan Coordination tools promote care quality by coordinating the continuity and coordination of care across all clinical disciplines and sectors involved in a patient’s treatment. These tools:
  • Provide an integrated view of all plans of care, for each episode of care for each patient, across the entire care continuum
  • Give all providers an overall view of the patient’s episode of care, regardless of the number of practitioners or institutions involved in providing that care
  • Alert providers when conflicts between plans of care are found, and enforcing negotiation among the practitioners involved to resolve such conflicts.

Case Management Tools

Functional categories: Information input, storage, and access; Decision support - treatment coordination and execution

Case management tools support case managers in working with high-risk patients/clients across the entire continuum of care by helping them perform their tasks efficiently and effectively, including documenting patient needs and status, and alerting them when action is required. In the acute care environment, case management tools typically rely upon clinical guidelines and pathways throughout the continuum of care.[32] Advanced tools also evaluate the outcomes of the case management process, such as the costs and benefits of these services.

As with the other HIT tools, the functions case management software provides vary widely from one vendor to another. And since case managers work in many there are many different healthcare environments, there are numerous types of case management tools, ranging from geriatric care to helping chronically and severely mentally ill outpatients find housing and receive the care and support they need.[33]

Care Order Management System (COMS)

Functional category: Decision support - treatment coordination and execution, alerts, process and outcome evaluation

The Care Execution Management (COMS) tool promotes care quality in two ways:
  • It monitors plan of care execution and alerts clinicians when orders are not carried out in a timely manner, enabling adjustments to be made in the care plan so as to avoid adverse events
  • It enables the efficient allocation of time and hospital resources — including staff, facility and space — by helping assure plans of care are carried out as ordered with minimal disruption. It tracks each procedure for every patient, computes resource requirements against current capacities, and provides staff real-time information needed to accommodate all plan of care orders in a timely manner.

This unique (patent pending) tool works in conjunction with EHR, CPOE, and clinical pathways tools by providing the “brains” that analyze clinical data using rules and to making decisions about plan of care execution. When if determines that care is not delivered according to the practice guidelines thereby putting the patient at risk, it triggers a process by which clinicians working with the patient are notified in a timely manner about the situation, and given the information they need to rectify the problem.

Research, Modeling, and Knowledge Management Tools

Functional category: Knowledge development

A wide variety of tools are in the research, modeling, and knowledge management category. The include tools for statistical analysis, concept management, development and exchange of healthcare treatment and financial models, document management, strategy development, collaborative decision tools, idea management, text mining, inferential logic tools, and more.

In the Quality though Knowledge model, these tools are important for researchers, modelers, and knowledge service specialists to use when, for example:
  • Evaluating process and outcomes data, and examine clinical observation and lessons learned in order to validate and develop evidence-based practice guidelines
  • Creating and evolving knowledgebases of evidence-based practice guidelines, along with reference and training materials
  • Extracting key concepts from the scientific literature in order to develop taxonomies for organizing and searching information contained in databases and document files
  • Guiding group decisions for developing and revising practice guidelines
  • Examining data from the field for biosurveillance and post-market drug surveillance (discussed next).

Biosurveillance and Post-Market Drug & Medical Device Surveillance Tools

Functional categories: Diagnostic decision support of the health of populations.

Biosurveillance and post-market surveillance were discussed earlier. Some characteristics of the ideal tools follow.

Bioresponse via the Public Accountability Knowledge System

An ideal biosurveillance system for first responders — people first on the scene of an emergency, such as police officers, firefighters, and health professionals — is the Public Accountability Knowledge System (PAKS), which is patent pending. The blueprint for the PAKS includes equipping each first responder with small monitors that wirelessly transmit victims’ vital signs and other detailed information to their EHRs. At the same time, other monitors would keep track of the first responder’s own vital signs and GPS location, should the person be in peril and need help. In addition, there would be sensors that monitor the environment for victims, toxic gases, biologic pathogens, etc., all of which is sent automatically to designated individuals and systems.

As our country moves incrementally toward a viable homeland security posture, a technology like PAKS is vital to provide information about the location of a disaster, victim health, and how a first responder could safely extract the victims. PAKS would be used to find disaster victims and to support a first responder, life saving healthcare delivery process. The first responder and the community affected by a disaster would integrate PAKS capability at a command-control vehicle and communications facility.

Once an organization performed a vulnerability and threat assessment, PAKS would be deployed. The information received and processed by PAKS includes:
  • Building Intelligence Tactical System [BITS] data. BITS — a computer-based program designed to provide the fire service with decision-based data about the buildings within their response areas.
  • EHR data sets in whatever format they are needed
  • Personal Health Information Network (PHIN) — a computer-based program designed to provide fire service with the most recent medical data describing the victim, their specific medical condition and a means to facilitate tracking between and among triage centers and emergency rooms
  • CodeBlue system MoatTrack information — for first responder tracking at a disaster site
  • Feedback from a novel Event Alarm Sensor Tracking (EAST) — wireless hardware device that is strategically placed on campus or within a building, which tracks and accounts for all individuals/victims during a disaster and after an emergency evacuation has been completed.

Post-Market Surveillance Tools

Such tools should support decisions by evaluating the safety and cost-effectiveness of medications medical devices after being introduced into commerce. They should provide a quick and easy way to collect, aggregate, analyze, and disseminate clinical and financial data on any pharmaceuticals and equipment.[34]

Business Intelligence tools

Functional category: Business decision support.

Business intelligence tools help improve business decisions for gaining sustainable competitive advantage using a wide variety of software applications for gathering, storing, analyzing, and providing access to business data. Common functions of these tools include query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.

Payers use business intelligence tools to analyze data from member, employer and provider transactions to make decisions about strategies for managing risk, increasing operational efficiency, controlling costs, improving member satisfaction in order to increase your bottom line results.

Healthcare providers (administrators, managers, and caregivers) use business intelligence tools to make decision that enable them to respond and adapt to changing requirements quickly and accurately for greater levels of business agility. The tools can help them evaluate and understand data about referrals sources, profitability of units and procedures, expenditures, etc.

Continuous Survey Readiness Tools

Continuous survey readiness products help hospitals and other healthcare organizations stay ahead of the accreditation cycles and unannounced visits of regulatory agents such as JCAHO and CARF.

A Complete HIT Decision-Support System: Linking the Diagnostic Aid, EHR, CPOE, Clinical Pathways, and COMS

Following is a brief description of how several of the HIT tools described above can be used together in a complete decision-support system:

  1. The patient and provider enter diagnostic information into the Diagnostic Aid tool, which accesses the patient’s EHR, processes all the data, and recommends one or more possible diagnoses.
  2. The provider using the Diagnostic Aid tool to select (with a mouse-click) the most appropriate diagnosis, possibly after doing further testing and entering the result. The tool then recommends one or more possible clinical pathways based on the diagnosis, patient characteristics, and other data from the EHR. Each recommendation includes evidence-based information justifying it, along with instructional materials for the provider and patient decision aids.
  3. The patient and provider discuss the treatment options and agree on a particular clinical pathway. The provider then mouse-clicks the pathway of choice using the Diagnostic Aid tool, which then automatically sends the selection to the Clinical Pathways tool.
  4. The Clinical Pathways tool then sends the particular orders contained in selected practice guideline to the pathway to the CPOE. These are considered the “standing orders,” i.e., a standard, yet flexible, course of treatments and tests a patient with a given diagnosis receives unless a physician changes or augments any of the orders.[35]
  5. The physician confirms each order by mouse-clicking the CPOE, and types in any changes. It now becomes the plan of care, which is automatically sent to the EHR. Treatment then begins.
  6. As the appropriate clinicians complete each order, they use a corresponding CPOE on their handheld computerized device, PC tablet, or desktop computer to indicate the order was done. The CPOE timestamps each executed order and sends the results to the COMS.
  7. The COMS then access the Clinical Pathways tool to determine if the order way done on time or if it was done too early, too late, or not at all (i.e., was at variance). If an order was at variance, all clinicians involved are alerted immediately, the patient’s physician makes any necessary adjustments using the CPOE. In addition, the reasons for the variance are mouse-clicked by the clinician. The COMS then automatically modifies the plan of care accordingly and updates the EHR.
  8. Upon discharge, the Clinical Pathways tool computes the clinical and financial outcomes, and generates a report of the outcomes and variances and reasons for the patient’s episode of care, as well as variances for all episodes of care for all patients during the current year and across years.

Blog/Wiki links:
» The Clinical Informatics Wiki -- Clinfowiki -- Contains additional information defining EMRs, CPOEs, and Clinical Decision Support

Next: Network Architectures

Footnotes and References

{1} [1] Chaudhry, B., et al. (May, 16). 2006Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care. Annals of Internal Medicine; 144(10). Available at
[2] Clancy, C.M. & Cronin, K. (2005), Evidence-Based Decision Making: Global Evidence, Local Decisions. Health Affairs; 24 (1): 151-162. Available at
[3] The Use of Computers in Health Care Can Reduce Errors, Improve Patient Safety, and Enhance the Quality of Service - There Is Evidence. (2005). Available at the NHS Connecting for Health web site at
[4] Bates, D.W. et al. (2003). Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality. Journal of the American Medical Informatics Association, 10 (6). Available at
[5] Kennedy, G. (2006). Effective Clinical Decision Support. HealthIT World News. Available at
[7] Connecting for Health press release (February 8, 2006). Connecting for Health Prototype Successfully Moved Electronic Health Information Among Medical Record Systems in Three States on Three Independent Networks. Available at
[8] Computerized Health Agents — which use a patented underlying technology — are part of the NHDS Hii Interoperability Platform at
[9] See, for example, The Patient Privacy Coalition web site at
[10] See the NHDS MultiCryption™ technology at
[11] For more information about Diagnostic Aids, see the OpenClinical web site at,
[12] Burger, C.S. The Use of Problem Knowledge Couplers in a Primary Care Practice. Available at
[13] Liebel, D. and Friedman, B. (1999), Problem Knowledge Coupler Use Pilot Project. Available at
[14] Information managed by EHRs may include patients' problems/symptoms, diagnoses, vitals, clinician observations, allergies, lab test results, medications, inoculations, radiology results/reports, pathology results/reports, mental status, psychological evaluation result, prior illnesses and treatments, traumas (physical and psychological).
[15] Tang P. (2003). Key Capabilities of an Electronic Health Record System. Letter Report. Institute of Medicine Committee on Data Standards for Patient Safety. Board on Health Care Services. Washington D.C.: National Academies Press.
[16] For more information about EHRs, see the OpenClinical web site at
[17] Brailer, D.J. and Terasaw, E.L. (2003). Use and adoption of computer-based patient records. California HealthCare Foundation. Available at
[18] Walker, J, et al. (2004) The Value of Health care Information Exchange and Interoperability. Boston (MA): Center for Information Technology Leadership. Available at
[19] Ventres, W., et al. (March, 2006). EHRs in the Exam Room: Tips on Patient-Centered Care. American Academy of Family Physicians. Available at
[20] Americans want benefits of personal health records. Markle Foundation (June 5, 2003). Available at
[21] Kaushal, R. and Bates, D.W. (2001) Computerized Physician Order Entry (CPOE) with Clinical Decision Support Systems. Agency for Healthcare Research and Quality (AHRQ). Available at
[22] Lee, J. (2002). Computerized Physician Order Entry (CPOE) Systems," Research Synthesis, AcademyHealth. Available at
[23] Assessing IT Value: Ambulatory Care Order Entry. Center for IT Leadership (CITL) - Partners HealthCare System Boston (2003). Available at
[14] Koppel, R. et al. (2005). Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors. JAMA;293:1197-1203. Available at
[25] Wang, D., et al. (2001) Representation of Clinical Practice Guidelines for Computer-Based Implementation. Medinfo, London, UK. Available at
[26[ Open Clinical web site at
[27] Mottur-Pilson, C. Clinical Practice Guidelines: Friend or Foe? American College of Physicians. Available at
[28] Open Clinical web site at
[29] Should You Be On A Patient Pathway? Yale-New Haven Hospital web site at
[30] Open Clinical web site at
[31] See the CarePathWays Plus tool at the NHDS web site at
[32] Marietti, C. (1997). Destination: Quality Care and Cost Management. Healthcare Informatics. Available at
[33] See the NHDS case management tool at
[34] See the Hii™ Post-Market Drug Surveillance tool at
[35] Crute, C. (December 2005). Case Study: Achieving High-Quality Care at Reid Hospital & Health Care Services. The Commonwealth Fund; 14. Available at

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