US20140200907A1 - Method of optimizing healthcare services consumption - Google Patents

Abstract

A method of optimizing healthcare services consumption according to the invention includes the steps of assessing the healthcare situation of an employer providing healthcare benefits to a population, identifying a first group of patients from the population likely to generate expensive healthcare claims based on data representing past claims, periodically determining whether patients in the first group have satisfied certain predetermined healthcare requirements, identifying a first group of providers who provide high quality, cost efficient healthcare services based on the practice patterns of the providers, prompting patients who have not satisfied the predetermined healthcare requirements to obtain services from providers in the first group, and responding to healthcare requests from patients by determining whether the requesting patient is seeking services from a provider in the first group, and, if not, urging the patient to obtain such services from a provider in the first group.

Description

RELATED APPLICATION
• This application is a continuation of and claims priority to U.S. patent application Ser. No. 13/178,174, filed Jul. 7, 2011 entitled “Method of Optimizing Healthcare Services Consumption,” which is a continuation of U.S. patent application Ser. No. 12/773,334, filed May 4, 2010, now U.S. Pat. No. 8,036,916 entitled “Method of Optimizing Healthcare Services Consumption,” which is a continuation of U.S. patent application Ser. No. 10/313,370, filed Dec. 6, 2002, now U.S. Pat. No. 7,711,577 entitled “Method of Optimizing Healthcare Services Consumption,” the entire disclosures of which are expressly incorporated herein by reference.
FIELD OF THE INVENTION
• The present invention generally relates to a method of optimizing healthcare services consumed by patients including employees and their family members by improving the overall quality of care and reducing the overall cost incurred by the employer, and more particularly to a method for application by a healthcare quality management firm (HQM) of characterizing the healthcare situation of an employer who pays for healthcare, comparing that healthcare situation to that of a geographic area in which the employer resides, identifying factors affecting the quality and cost of the healthcare, and recommending action for addressing the factors by applying resources at levels corresponding to the relative affect of the factors on the quality and cost of the healthcare.
BACKGROUND OF THE INVENTION
• Employer sponsored healthcare benefits are of tremendous value to employees and their families. Such benefits, on the other hand, typically constitute a significant portion of an employer's total operating costs. Unfortunately, as medical costs continue to increase, the cost of providing employer sponsored healthcare benefits will continue to increase.
• Currently, many employers attempt to offset the rising costs of providing healthcare benefits by shifting the cost to employees. Of course, only so much of the expense can be shifted to employees. At some point, the cost incurred by the employees will become prohibitive, and employer sponsored healthcare will no longer be seen as a benefit. Some employers attempt to monitor the price of certain healthcare services, but without information relating to the quality of the services, cost information is of limited value. Other employers have attempted to reduce their healthcare expenses by sponsoring health fairs or wellness screenings. This approach, while somewhat effective in prompting preventative healthcare, is not a focused expenditure of resources. For the majority of employees who are healthy, the money spent on wellness screenings is essentially wasted. Finally, employers sometimes attempt to negotiate the fixed costs associated with administering healthcare benefits. Again, since these costs typically make up only a small portion of the total cost, even successful negotiation attempts will have a limited impact on the employer's bottom line.
• In short, employers have been largely unsuccessful in their attempts to control healthcare costs while ensuring a high level of care. Employers simply lack the information necessary to identify the most significant factors affecting their healthcare costs, to quantify and compare the performance of healthcare providers, and to apply their resources in a way that most effectively reduces both the overall consumption of healthcare and the costs of the services consumed while maintaining or improving the quality of the healthcare benefits they provide.
SUMMARY OF THE INVENTION
• The present invention provides a method of optimizing healthcare services consumption through analysis of the demographic and wellness characteristics of an employee population (including employees and employee family members, hereinafter, “patients”), analysis of the quality and cost efficiency of the practices of providers used by the patients, and intervention with patients and providers to improve the overall health of the patients, the practices of the providers, and the cost efficiency of the employer provided healthcare plan. The method, in one embodiment thereof, includes the steps of assessing the healthcare situation of the employer as it relates to normative characteristics of a health economic zone including the patients, identifying patients from the covered population likely to generate expensive healthcare claims relative to the other patients based on data representing past healthcare claims generated by the patients, periodically determining whether these patients have obtained healthcare services that satisfy predetermined requirements, identifying qualified providers in the health economic zone who provide high quality, cost efficient healthcare services relative to other providers in the health economic zone based on data representing past practice patterns of the providers, prompting patients who have not obtained healthcare services that satisfy the predetermined requirements to obtain additional healthcare services from the qualified providers, and responding to healthcare requests from patients by determining whether the requesting patient is seeking to obtain healthcare services from a qualified provider, and, if not, urging the patient to obtain services from a qualified provider.
• The features and advantages of the present invention described above, as well as additional features and advantages, will be readily apparent to those skilled in the art upon reference to the following description and the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
• FIG. 1 is a conceptual diagram of participants in a healthcare consumption situation that may be optimized using a method according to the present invention.
• FIG. 2 is a conceptual diagram of an interrelationship between a central database and the participants shown inFIG. 1.
• FIG. 3 is a flow diagram depicting steps included in one embodiment of the present invention.
• FIG. 4 is a conceptual diagram of a health economic zone.
• FIGS. 5-15 are illustrations of reports generated according to an embodiment of the present invention.
• FIG. 16 is a flow diagram of a process for evaluating the practice characteristics of healthcare providers.
• FIG. 17 is a flow diagram depicting steps included in one embodiment of the present invention.
DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION
• The embodiments described below are merely exemplary and are not intended to limit the invention to the precise forms disclosed. Instead, the embodiments were selected for description to enable one of ordinary skill in the art to practice the invention.
• FIG. 1 depicts a relationship among participants in a typical employer provided healthcare situation. In this example, theemployer10 is self-insured and provides funds, based on predicted healthcare costs, to a third party administrator (TPA12) of healthcare benefits for paying employee healthcare claims. Of course, also involved in this relationship are the healthcare consumer,patient14, the healthcare provider16 (e.g., a physician or a facility such as a hospital, laboratory, etc.), apharmacy18, a pharmacy benefit manager (PBM19), aPPO20, and a healthcare quality management firm (HQM13). As should become apparent from the following description,HQM13 could perform the functions ofTPA12. Thus, except where expressly indicated otherwise or mandated by the context of this description, references toHQM13 may includeHQM13 and TPA12.
• In a typical transaction associated with a healthcare claim,patient14visits provider16 to obtain healthcare services and/or products such as drugs. For simplicity, this description collectively refers to services and products as healthcare services.Provider16 submits a claim to PPO20 (or alternatively directly to TPA12) in an amount corresponding to the cost of the services.Provider16 may also write a prescription that is received by apharmacy18. In that event,pharmacy18 submits a claim to PBM19, which in turn submits a claim to TPA12. As is well known in the art, PPO20 (or alternatively TPA12) typically discounts or reprices the claimed charges based on an agreement betweenprovider16,pharmacy18, andPPO20. The repriced claim is submitted toTPA12 for payment. TPA12 accesses funds in the healthcare account ofemployer10 to payprovider16 andPBM19 the repriced claim amounts. PBM19 then forwards a payment topharmacy18. TPA12 then also informspatient14 of the patient's payment responsibility that arises as a part of the application of the terms of the underlying benefit plan when it does not pay 100% of eligible charges.Patient14 then sends a payment toprovider16. The above-described example assumes that TPA12 is separate fromHQM13. IfHQM13 functions as a combination ofHQM13 andTPA12, thenHQM13 interacts directly withemployer10,patient14,provider16,PBM19, andPPO20 in the manner described with reference toTPA12 above.
• As should be apparent from the foregoing, throughout each such transaction, TPA12 has access to all of the material claim information. TPA12 shares this information withHQM13, which may contactemployer10,patient14, and/orprovider16. Accordingly, as will be described in detail below,HQM13 is in a position to facilitate change in and/or directly influence the healthcare situation to control the cost incurred byemployer10 and to encourage consumption of healthcare fromhigh quality providers16. Thus,HQM13 is described below as practicing the present invention as a service for the benefit of its clients,employers10, andpatients14 including the clients' employees and their family members.
• According to one embodiment of the present invention, TPA12 maintains adatabase22 including a variety of different types of information fromemployer10,provider16,PBM19, andPPO20 as depicted inFIG. 2. As is further described below, TPA12 also updates information included indatabase22 as a result of its interaction withHQM13.Database22 may be maintained on any of a variety of suitable computer-readable media such as a hard drive of a computer. WhileFIG. 2 suggests contributions of information todatabase22 by each ofemployer10, TPA12,provider16, PBM19, andPPO20, it should be understood that such information may not be provided directly todatabase22. Instead,TPA12 may receive information from the other participants and enter and/or otherwise process the information for storage indatabase22. For example, information may be transferred electronically fromemployer10,provider16,PBM19,PPO20, andHQM13 toTPA12 via a network or multiple networks. Moreover,TPA12 may physically reside at multiple locations, each of which receives information from the other participants. Such multiple locations may be connected together via a network configured to permit simultaneous access todatabase22 through a server. Any suitable method of transferring information and storing such information in either a centralized or distributeddatabase22 is within the scope of the invention. For simplicity, the transfer of information is described herein as occurring electronically over a network, anddatabase22 is described as a centralized database accessible by asingle TPA12 location.
• As is further described below, the information stored indatabase22 permits HQM13 to evaluate the healthcare situation ofemployer10, including the cost information, the healthcare characteristics ofpatients14, and the performance ofproviders16 used bypatients14 covered under the healthcare plan provided byemployer10. Accordingly, the information indatabase22 includes employer information, patient information, provider information, pharmacy information, and claims information that may relate to some or all of the other types of information. The employer information includesinformation identifying employer10,patients14 covered under the employer provided healthcare plan,PPO20 associated withemployer10, as well as historical data that characterizes changes in the healthcare situation ofemployer10 over time. The patient information includes the name, address, social security number, age, and sex of each patient14 covered under the healthcare plan provided byemployer10. The provider information includes the name, tax identification number, address, and specialty of a plurality of healthcare providers across a large geographic region, such as the entire United States. As is further described below, portions of theprovider10 information are associated withemployer10. These portions correspond to theproviders16 that provide services topatients14. The pharmacy data includes information identifying the type, quantity, and dosage of drugs associated with a particular prescription for aparticular patient14 as well as the social security number of thepatient14. This information permits association of prescription drug claims withpatients14. These claims can be further associated with theprovider16 that wrote the prescription by accessing the claims data (described below) associated with the patient14 who filled the prescription to determine whichprovider16patient14 saw prior to obtaining the prescription. Alternatively, an identifier may be included in the pharmacy data with each prescription entry that identifiesprovider16.
• The claims data stored indatabase22 include portions of the above-described data, but may be organized or associated with a particular claim. More specifically, a claim may include information identifying and/or describingemployer10,patient14,provider16,pharmacy18,PBM19, andPPO20. The claim may further include information describing the condition or symptoms ofpatient14 that generated the claim, the diagnosis ofprovider16, the procedures ordered byprovider16 to treat the diagnosed condition as identified by commonly used procedure codes, and the costs (both original charges and repriced amounts) of the healthcare services associated with the claim.
• As indicated above, the information stored indatabase22 comes from a variety of sources. For example, when anemployer10 becomes a new client ofHQM13,PPO20 servicingemployer10 may provideHQM13 with enrollment data including employer information, employee information, and associated past claims information.HQM13 may then process that information for addition todatabase22. Periodically,PPOs20 ofemployers10 transfer claims information to TPA12 (i.e., as the claims information is processed by PPOs20). As indicated above, in addition to information relating to associated healthcare services, this claims information may include employee information, provider information, and pharmacy information. Additionally, PBMs19 (or data transfer services working with PBMs19) periodically transfer pharmacy information toTPA12. As further described below, each time new information is provided toTPA12,TPA12 and/orHQM13 may process the information such that it is associated with aparticular employer10, aparticular patient14, or aparticular provider16.
• Referring now toFIGS. 3 and 4, one embodiment of the method according to the present invention may be generally described as involving three basic steps: analyzing the healthcare situation ofemployer10, improving the healthcare consumption characteristizcs ofpatients14, and improving the overall performance characteristics ofproviders16 used bypatients14. One process for analyzing a healthcare situation of anemployer10 is depicted inFIG. 3. In general, after all of the relevantinformation regarding employer10,patients14 associated withemployer10, andproviders16 used bypatients14 resides indatabase22,HQM13 executes software (as further described below) to accessdatabase22 and identify a Healthcare Economic Zone (HEZ24,FIG. 4) corresponding to employer10 (step26). As shown inFIG. 4,HEZ24 corresponds to a geographic area that includes allpatients14 associated with allemployers10 andproviders16 used by patients14 (includingphysicians28 andfacilities30, such as hospitals).HEZ24 may be defined to correspond to Hospital Service Areas set forth by the Dartmouth Atlas project, a funded research effort of the faculty of the Center for the Evaluative Clinical Sciences at Dartmouth Medical School. Essentially, HEZs are based on the zip codes of the residential addresses ofpatients14 stored indatabase22 and the locations ofproviders16 servicing those zip codes. In other words, anHEZ24 includes a geographic region in whichpatients14 tend to obtain their primary healthcare. For example, assumingpatients14 associated withemployer10 all reside in three adjacent zip codes that are serviced by one facility30 (also within one of the three zip codes), then those three zip codes are included inHEZ24. However, iffacility30 also referspatients14 to, for example,specialist providers16 in a fourth zip code, then the fourth zip code is also included inHEZ24.FIG. 4 showsHEZ24 fully contained within a larger geographic area such as astate32. It should be understood, however, that HEZs24 (or the equivalent of HEZs24) may extend across state lines.
• Referring again toFIG. 3,step34 indicates that information indatabase22 corresponding to employer10 (i.e., employer information, patient information, claims information corresponding topatients14 associated withemployer10, and provider information) is analyzed to evaluate the healthcare situation ofemployer10. Instep36, the employer specific data is compared to generalized data relating toHEZ24 as is further described below. As indicated inFIG. 3, the results of the analyses performed insteps26,34, and36 may be processed in the form of provider reports38, employer reports40, andpatient reports42, some or all of which may be provided toemployer10 as shown inFIG. 1 as part of the process of analyzing the healthcare situation ofemployer10.Step44 depicts the process of updatingdatabase22 asHQM13 and/orTPA12 receive claims information and/or changes in the population ofpatients14 associated withemployer10 as a result of employees being hired by or departing fromemployer10, or changes in the family situation of the employees. As should be apparent from the figure, the process of analyzing the healthcare situation ofemployer10 is therefore continuously updated and may result in generation of periodic reports foremployer10 andHQM13 to track changes in the healthcare situation over time.
• FIG. 5 depicts an example of anemployer report40. Althoughchart46 ofFIG. 5 does not compareemployer10 information toHEZ24 information, it is anemployer report40 because it providesemployer10 information regarding the costs of healthcare services in theHEZ24 in which employer10 (more accurately,patients14 associated with employer10) resides.Chart46 includes aspecialty column48, a total allowed charges column50, a total allowed charges atnormative costs column52, a percent of excess charges column54, and an excess charge per life peryear column56.Chart46 providesemployer10 information regarding the relative costs of healthcare services (by specialty) in the employer'sHEZ24 as compared to the costs in a larger geographic area that includes HEZ24 (e.g.,state32, the Midwest, the southeast, etc.). In this example,providers16 inHEZ24 charged $4,251,526 (column50) for cardiology services over the course of a predetermined time period, such as two years.Column52 shows that the normative costs for such services is $4,488,559 for the same number of healthcare consumers (i.e., patients14) over the same predetermined time period. More specifically, the dollar amounts incolumn52 are derived by first adding all of the charges for cardiology services in the larger geographic area for the predetermined time period and dividing the total by the number of healthcare consumers in the larger geographic area. Then, this “average cardiology charge per healthcare consumer” is multiplied by the number of healthcare consumers inHEZ24. As shown in column54,HEZ24 experienced cardiology costs that were 5.3 percent below the normative cardiology charges. Finally,column56 simply converts the percentage deviation from the normative charge into a dollar value divided by the number of healthcare consumers inHEZ24 and the number of years in the predetermined time period.
• Line58 shows the totals for all specialties or Major Practice Categories (MPCs).Lines60 and62 illustrate a situation whereinHEZ24 is serviced by more than onePPO20. Since all of the claims information indatabase22 is associated with aparticular PPO20, the charges associated with all claims of healthcare consumers inHEZ24 corresponding to PPO network A and PPO network B may be separated based on the PPO that handled the claim. Thus,lines60 and62 depict the relative usage of the PPOs by healthcare consumers in HEZ24 (column50), the normative usage values for each PPO in a larger geographic area (eg., state32) (column52), the cost performance of the PPOs forHEZ24 relative to the cost performance of the PPOs across state32 (column54), and the meaning of that relative performance on a dollars perpatient14 per year basis (column56).Lines64 and66 provide similar information for two hospitals used by healthcare consumers inHEZ24.
• As should be apparent from the foregoing,employer10 may readily scan down total allowed charges column50 to determine the specialties most likely to contribute significantly to the employer's overall healthcare costs.Columns54 and56permit employer10 to readily identify those practice categories having charges that deviate most from the average or normative charges. In this manner, employer10 (and HOM13) can isolate the practice categories that have the most potential for providing the most significant reduction in the overall healthcare costs ofemployer10.
• Another employer report40 (chart68 ofFIG. 6) follows the same format aschart46, but compares the actual healthcare costs ofemployer10 to the typical costs inHEZ24.Chart68 includes aspecialty column70, a total costs column72, a normalized costs inHEZ24column74, apercent excess column76, and an excess cost per life per year column78. Column72 represents thetotal costs employer10 incurred for the various specialties listed incolumn70 during a predetermined time period. The normalized amounts incolumn74 represent the expected cost inHEZ24 for an employer having the same number ofpatients14 as are associated withemployer10. For example, assuming a total cost for cardiology inHEZ24 of $17,122,789 for 35,623 healthcare consumers inHEZ24, the average cardiology cost per healthcare consumer is $480.67. Assuming thatemployer10 has 150patients14, then the expected total cost for cardiology services (i.e., the normalized costs inHEZ24, column74) is $72,100. Accordingly,employer10 has incurred costs for cardiology services that are 23.7% below the anticipated amount for an employer the size ofemployer10 located inHEZ24 as shown bycolumn76. Column78 reflects this percentage in a perpatient14 per year dollar value.
• As should be apparent from the foregoing, chart68 could readily be revised to reflect similar information for actual consumers of the particular specialties as opposed topatients14 and healthcare consumers generally. In other words, if only ninepatients14 used cardiology services over the predetermined time period (resulting in a total cost of $55,000),column74 could be modified to reflect the expected amount for nine of the average consumers of cardiology services inHEZ24 over the predetermined time period. Of course,columns76 and78 would then reflect the difference between these values on a percentage and per life per year basis, respectively.
• FIG. 7 is anotheremployer report40 that summarizes the illness burden and demographics ofHEZ24 associated withemployer10. Chart80 includes adescription column82, anHEZ24data column84, a normative value a larger geographicarea including column86 forHEZ24, apercent excess column88, and an excess per life peryear column90. It is well known that healthcare consumption is greater for adults verses children (other than newborn children), for females verses males, and for older adults verses younger adults. Obviously, healthcare consumption is also greater for individuals having certain types of pre-existing illnesses as compared to healthy individuals. The method of the present invention uses these factors to compute a healthcare index (line92 inFIG. 7) forHEZ24 in whichpatients14 associated withemployer10 reside. The method of the present invention calculates the healthcare index for anHEZ24 using Episode Risk Group (ERG) scores inherent in the health risk assessment process provided by Symmetry Health Data Systems, Inc. and described in “A New Approach to Health Risk Assessment,” a white paper available from Symmetry Health Data Systems, Inc., the disclosure of which is hereby incorporated herein by reference. A healthcare index for each patient14 inHEZ24 is computed using a retrospective analysis, and the index forHEZ24 is derived by calculating an average index for allpatients14 inHEZ24. As shown incolumn84 ofFIG. 7,HEZ24 has 9,808patients14 having an average age of 42, and comprising 74.8% adults, 38.6% of whom are female. These factors result in a healthcare index forHEZ24 of 1.506. As shown incolumn88, this healthcare index is 50.6% above the normative healthcare index of 1.0 for the larger geographic area. This high healthcare index results from a higher than typical percentage of females and adults inHEZ24 and a higher than typical percentage of individuals with health risk factors. More specifically, as shown incolumn88 ofFIG. 7, 10.8% of the overage is due to atypical demographics (i.e., an older and more heavily female population). 39.8% of the overage is due to the atypical illness burden of the population (i.e., a population with health conditions corresponding to higher than typical health risk factors). Accordingly, anemployer10 inHEZ24 should expect to have healthcare costs that are greater than the typical costs of the larger geographic region. It should be understood that a similar report could readily be generated comparing the illness burden and demographic information of aparticular employer10 to information describing theHEZ24 in whichpatients14 associated withemployer10 reside.
• Referring now toFIG. 8, apatient report42 is shown summarizing the chronic illnesses ofpatients14 associated withemployer10. It is well known that typically 80% of an employer's healthcare costs are generated by approximately 20% of the covered population ofpatients14. That 20% of the population generally has a high incidence of chronic illness. Accordingly, chart94 ofFIG. 8 is generated to provide employer10 a summary of its chronicallyill patients14.
• As shown,column96 lists various chronic illnesses. While the method of the present invention may track any number of chronic illnesses, only six are shown inFIG. 8.Column98 shows the number ofpatients14 having each of the listed illnesses.Column100 shows the number of thosepatients14 listed incolumn98 that have at least one year of claims history (i.e., have submitted claims that were added to database22).Column102 shows the number ofpatients14 that have satisfied the minimum annual care requirements (MACRs) recommended for treating the chronic illness or illnesses from which they suffer.Column104 simply expresses the number incolumn102 in the form of a percentage of thetotal patients14 suffering from the listed illness. The MACRs for each chronic illness ofchart94 are listed incolumn106 and obtained using software available from McKesson Corp., a supplier of information and managed care products and services for the health care industry. In particular, McKesson's CareEnhance Resource Management Software (CRMS) provides such information. As the method of optimizing healthcare services consumption described below is practiced, periodic reports such aschart94 ofFIG. 8 will show improvements in the number ofpatients14 that satisfy the MACRs associated with their particular illness(es).
• Chart110 ofFIG. 9 shows the chronic illness status ofpatients14 associated withemployer10 in terms of co-morbidities.Chart110 includes adescription column112, a currentpatient column114, a percent of currentcovered patients column116, a previouspatient column118, a percent of previouscovered patients column120, and a percent of database driven norms column122. As shown incolumn114, of the 993total patients14 covered under a healthcare plan provided byemployer10, a total of 619 have a single chronic illness, 236 have two chronic illnesses, 86 have three chronic illnesses, etc.Column116 expresses the number ofpatients14 listed incolumn114 in terms of the percentage of thetotal patient14 population.Columns118 and120 include similar information representing the status of the chronically ill at a previous date.Employer10 can monitor changes in the chronic illness status of itspatients14 by comparing these two sets of columns. Finally, column122 shows the typical percentage of individuals (based on all individuals reflected in the database) with the particular number of chronic illnesses.
• In addition to summarizingpatients14 having chronic illnesses, the method of the present invention also includes the step of performing a risk stratification of allpatients14 covered byemployer10. The results of this risk stratification step are provided toemployer10 as anpatient report40. Chart124 ofFIG. 10 is an example of such anpatient report42. As shown, chart124 includes a familyidentification number column126, apatient identification column128, anage column130, agender column132, ahealthcare index column134, and a predictedcost column136. The primary purpose ofchart124 is to displaypatients14 in order of their associated healthcare index listed incolumn134. The healthcare index is derived using the McKesson CRMS software as described above, which takes into account the age, gender, chronic illnesses, and co-morbidities of each patient14. Also, by analyzing claims data describing prescriptions, the CRMS software imputes illnesses ofpatients14 based on the number and types of medications prescribed forpatients14. Thus, the healthcare index is used to rankpatients14 in terms of their likelihood of generating large medical expenses in the near future. It should be noted that not only the chronically ill are identified by the healthcare index.Other patients14 having conditions that are not considered chronic may have high healthcare indices.Column136 provides a predicted cost associated with each patient14 based on their healthcare index. More specifically,column136 is derived by calculating the total expense associated with the normative population, and dividing that amount by the total number of ERG risk points of the normative population to get dollars per risk point (prospectively). Then, using the method of the present invention (and not the CRMS software), the healthcare index ofcolumn134 is multiplied by the dollars per risk point value.
• The above-described employer reports40 andpatient reports42 are illustrative of the way in which the method of the present invention determines whichpatients14 covered byemployer10 should receive intervention or proactive coaching (as further described below and depicted inFIG. 1), and at what level of intensity. In other words, since chronicallyill patients14 generally generate large healthcare costs, chronicallyill patients14 should be monitored and coached most actively and at levels corresponding to the number of chronic illnesses from which they suffer. Likewise,patients14 having high healthcare indices because of their age, gender, illnesses, etc. should be monitored and coached most actively and at levels corresponding to their healthcare index. Using the above-described approach,patients14 that require proactive coaching typically constitute approximately 25% of thetotal patient14 population. It has been shown that this 25% portion of the patient14 population typically generates 90% of the total healthcare costs incurred byemployers10.
• As indicated above, the method of the present invention also generates physician reports38 such aschart138 shown inFIG. 11.Chart138 is an example of a comparison of various characteristics of the practice of aparticular provider16 to the practices ofother providers16 in the same specialty. In order to make such comparisons, the claims information indatabase22 may be analyzed on the basis of “episodes” of healthcare. This analysis is performed using software applications available from McKesson Corp., which analyze the services and costs associated with claims originated by aparticular provider16. An episode is defined as a healthcare consumption sequence including all healthcare services consumed by apatient14 for a particular healthcare problem. Episodes may include healthcare services ordered by a physician as a result of an initial office visit (e.g., tests, X-rays, etc.), healthcare services associated with a subsequent hospital visit (e.g., for surgery), and healthcare services associated with aftercare or follow-up visits to the physician.
• The analysis of claims information grouped by specialty episodes permits identification ofproviders16 having practice patterns that result in low total costs for the types of healthcare problems they treat as compared toother providers16 in the specialty. Additionally,providers16 who deliver high levels of post-primary preventative care services for chronicallyill patients14 can be identified. Finally, specific undesirable characteristics of a provider's16 practice patterns can be identified such as up-coding, ordering inappropriate services, vague or invalid diagnostic codes, and services that are performed too frequently. All of this information is available from the 10 claims information stored indatabase22.
• Referring back toFIG. 11,Bar140 ofchart138 represents the percentage of procedures ordered by a particular provider16 (physician ID #223776) that were determined to be inappropriate for the diagnosis reflected in the claims information associated with the evaluated episodes.Bar142 represents similar data for the entire specialty. Comparingbar140 to bar142 shows that this particular anesthesiologist ordered inappropriate procedures at nearly double the rate of others in the specialty. The remainingbar groups144,146,148,150, and152 permit similar comparisons for the practice pattern characteristics indicated onchart138.
• As further described below, one of the steps of a method according to the present invention involves determining whetherproviders16 used byemployees14 ofemployer10 provide healthcare in a manner that satisfies certain criteria. If so, theseproviders16 are identified as Quality Service Providers or QSPs. To achieve a QSP designation or rating,providers16 must, based on claims information stored indatabase22, pass three screens or quantitative tests of the providers'16 performance or practice characteristics. Anyprovider16 who fails one or more of these tests is identified for purposes of practicing the present invention as a non-certified QSP (“NCQSP”).
• The first test (“the CEI test”) is primarily economic. Using claims information indatabase22, the software of the present invention generates a Cost Efficiency Index (CEI) for eachprovider16. The CEI represents the actual total cost of care provided and/or ordered byprovider16 for completed episodes, divided by the total average cost of such care for similar episodes treated byother providers16 in the specialty. In other words, the cost toemployer10 for the healthcare delivered and/or ordered byprovider16 for all completed episodes for allpatients14 is first extracted from the claims information indatabase22. Then, the total cost for all similar episodes handled by allproviders16 tracked indatabase22 is determined, and divided by the total number of episodes to arrive at an average cost per episode in the specialty. Finally, the average cost per episode forprovider16 is divided by the average cost per episode in the specialty to arrive at the CEI forprovider16. Ifprovider16 has a CEI that exceeds a predetermined threshold (e.g.,) 125% or more above that of others in the specialty of provider16) and is statistically higher that the average for the specialty (i.e., sufficient claims information is contained indatabase22 to calculate the CEI ofprovider16 with a statistically acceptable confidence level such as at the p 0.1 level), thenprovider16 failed the CEI test and will be designated a NCQSP. A sample report of the data used to complete a CEI analysis is shown inFIG. 12.
• The second test in the QSP rating process (“the service rate test”) evaluates the preventative care practices ofproviders16. As is well known in the field of medical care, preventative care services may significantly affect the overall cost of healthcare, particularly those services provided to treat chronic illnesses to prevent those illnesses from progressing or resulting in other health complications. The McKesson software permits extraction of data representing the number and types of preventative care services ordered byproviders16 for treatment of chronic conditions. In one embodiment of the invention, nineteen chronic conditions are tracked. To evaluate aparticular provider16, the data representing the preventative care services forprovider16 is extracted and compared (according to the method of the present invention) to a minimum number and particular types of services considered acceptable in treatment of the particular chronic conditions treated byprovider16. This analysis results in a service rate forprovider16. More specifically, the total number of services ordered for chronically ill patients treated byprovider16 is determined, and then divided by the number of services required for such patients to achieve compliance with the associated MACRs. This service rate, or fraction of recommended MACRs, is then compared to the typical service rate in the appropriate specialty. Ifprovider16 has a service rate that is both less than a certain percentage of the typical service rate (e.g., has ordered 75% or less of the services required to achieve compliance with the associated MACRs) and statistically significantly lower than the average for the specialty (i.e., a statistically significant sample size is available indatabase22 to obtain confidence at the p 0.1 level), thenprovider16 failed the service rate test and is designated a NCQSP. A sample report representing the results of a service rate analysis is shown inFIG. 13.
• The third test (the “practice patterns test”) involves an evaluation of the overall practice patterns ofproviders16. More specifically, the McKesson clinical software is used to extract the number of occurrences of up-coding, ordering inappropriate services, vague or invalid diagnostic codes, and services that are performed too frequently, both for theparticular provider16 being evaluated, and for the specialty as a whole. Each practice pattern category is evaluated according to the method of the present invention to determine whetherprovider16 practices in a manner that results in a practice patterns challenge rate that exceeds a predetermined multiple of the typical practice pattern percentages (e.g., 200% or more than the typical practice patterns) and is statistically significantly higher than the average percentages (e.g., at the p 0.01 level). If so,provider16 failed the practice patterns test and is designated a NCQSP. A sample report representing the results of a practice patterns analysis is shown inFIG. 14.
• According to the present invention,providers16 that pass each of the three tests are assigned a QSP designation, indicating thatproviders16 practice high quality medicine in a cost effective manner. As will be further described below, theseQSP providers16 are targeted by the present method for providing a maximum percentage of the overall healthcare consumed bypatients14 ofemployer10. In addition to the basic QSP/NCQSP distinction resulting from the above-described process,providers16 may be further ranked based on the results of the above-described tests. For example, the QSP category ofproviders16 may be divided into “A”level QSP providers16 and “B”level QSP providers16. “A”level QSP providers16 may be defined asproviders16 who have historical claims data indatabase22 representing at least five episodes of the relevant type (“sufficient episodic data”), pass the CEI test with a CEI of less than 100% of the typical CEI in the specialty, and pass both the service rate test and the practice patterns test. “B”level QSP providers16 may includeproviders16 who (1) do not have sufficient episodic data, or (2) have sufficient episodic data and pass all three tests, but with a CEI of greater than or equal to 100% of the typical CEI in the specialty.
• Similarly,providers16 falling into the NCQSP category may be further ranked relative to one another to provide an ordered listing of NCQSPs. For example, “C”level NCQSP providers16 may be defined asproviders16 who have sufficient episodic data, pass the CEI test, but fail one of the service rate or practice patterns tests (not both). “D”level NCQSP providers16 may be defined asproviders16 who have sufficient episodic data and (1) fail the CEI test with a CEI of less than 150% of the typical CEI in the specialty or (2) fail both the service rate and practice patterns tests. Finally, an “E”level NCQSP provider16 may be defined as aprovider16 with sufficient episodic data who fails the CEI test with a CEI that is at least 150% greater than the typical CEI in the specialty. Thus,providers16 may be categorized in levels “A” through “E.” This ranking permits targeting not only QSPs, but “A” level and “B” level QSPs, or NCQSPs that at least have the best relative rankings on the list of NCQSPs.
• Anotherexample provider report38 is shown inFIG. 15. Chart154 ofFIG. 15 is a listing of NCQSPs in descending order. The group of columns collectively assignedreference designation156 identifies theproviders16 by ID, name, and location. Column158 lists the number of episodes indatabase22 associated with eachprovider16.Column160 lists the above-described CEI for each listedprovider16. The greater the CEI listed incolumn160, the more significant the provider's deviation from the practice patterns ofother providers16 in the specialty. Consequently, thoseproviders16 listed near the top of chart154 will provide healthcare resulting in a greater cost toemployer10. In one embodiment of the invention, listings of NCQSPs such as chart154 are divided into thirds for purposes of practicing the invention as further described below.
• Referring now toFIG. 16, a flow diagram of the above-described process for assigning QSP or NCQSP designations toproviders16 is shown. Atstep162, claims information corresponding to aparticular provider16 is extracted fromdatabase22 to determine whetherprovider16 has sufficient episodic data (e.g., at least five episodes of the relevant type). If not, thenprovider16 is designated an unknown, “B” level QSP. Ifprovider16 has sufficient episodic data stored indatabase22, then each of the three above-described tests are performed as indicated atstep163. Atstep164, the results of the CEI test are analyzed. If the CEI is 125% or more greater than the typical CEI in the specialty and satisfies the above-described statistical significance criteria, thenprovider16 is marked as failing the CEI test (step165). Otherwise,provider16 is marked as passing the CEI test (step166). Similarly, the results of the practice patterns test are analyzed atstep167. Ifprovider16 has a service challenge rate of 200% or more than the typical rate in the specialty and satisfies the above-described statistical significance criteria, thenprovider16 is marked as failing the practice patterns test (step168). Otherwise,provider16 is marked as passing the practice patterns test (step169). Finally, the results of the service rate test are analyzed in a similar manner atstep170, andprovider16 is marked as failing (step171) or passing (step172) the service rate test as a result of the analysis.
• As shown atstep173, “A” level QSPs are identified asproviders16 who are marked as passing all three tests and achieved a CEI of less than 1. If aprovider16 is marked as passing all three tests, but has a CEI that is greater than or equal to 1, thenprovider16 is designated a “B” level QSP as indicated bystep174. The remainingproviders16 are NCQSPproviders16. Atstep175, the method of the present invention identifies “C” level NCQSPs atstep176 asproviders16 who are marked as passing the CEI test, but failing one of the other two tests (but not both). Atstep177, the lowest level providers16 (“E” level NCQSPs) are identified asproviders16 who are marked as failing the CEI test with a CEI of at least 1.5. Any remainingproviders16 are designated “D” level NCQSPs as indicated at step161. “D” level NCQSPs includeproviders16 who are marked as failing the CEI test, but with a CEI of less than 1.5, andproviders16 who are marked as failing both the service rate and practice patterns tests. This process of evaluatingproviders16 for purposes of determining QSP/NCQSP status and levels within each category is repeated periodically to maintain an updated listing indatabase22. It should be further understood that the particular numeric threshold values used in each of the three tests may readily be changed to affect the number ofproviders16 falling into each of the five levels without departing from the principles of the invention. The designations forproviders16 resulting from the above-described process are used to improve the quality and cost-efficiency of the healthcare services consumed byemployees14 ofemployer10 in the manner described below.
• Referring now toFIG. 17, a flow diagram representing a portion of a method for optimizing healthcare services consumption is provided. Atstep178, the claims information corresponding topatients14 is extracted fromdatabase22. Step178 results in the data necessary to identifypatients14 having chronic illnesses (step180) and to rankpatients14 according to the above-described risk stratification process (step182). As indicated above and shown inFIG. 1, the method of the present invention, in one form thereof, involves intervention withpatients14 by registered nurses and other staff ofHQM13. This intervention or proactive coaching follows one or both of the two paths depicted inFIG. 17. First, forpatients14 identified as having one or more chronic illness, the method of the invention determines atstep184, based on claims information associated withsuch patients14, whether the MACRs associated with the illness(es) have been satisfied. If the MACRs for aparticular patient14 have not been satisfied, then a representative of HQM13 (e.g., a registered nurse or other staff member)contacts patient14 to remindpatient14 of the need to schedule the healthcare necessary to satisfy the MACRs. This contact may be accomplished by any mode of communication including by phone, email, fax, mail, or any combination thereof. Preferably, the representative ofHQM13 has a live conversation withpatient14 to impress uponpatient14 the importance of satisfying the MACRs associated with the patient's chronic illness.
• Atstep188, the representative ofHQM13 may also contactprovider16 of healthcare services associated with the chronic illness(es) ofpatient14. As a result of this contact, the representative enlists the cooperation ofprovider16 in the effort to persuadepatient14 to satisfy the MACRs. As should be apparent from the foregoing, a goal of this intervention is to improve the health ofpatient14 and minimize the cost toemployer10 by avoiding the increased healthcare expenses typically accompanying untreated chronic illnesses.
• Steps186 and188 may result in the generation of a healthcare request. Specifically,patient14 may respond to contact by the representative ofHQM13 by scheduling an evaluation byprovider16 or other action toward satisfying the MACRs associated with the chronic illness(es) ofemployee14. Step190 represents the possibility that a healthcare request is generated. If so, the healthcare request is processed as described below with reference to the second path depicted inFIG. 17. Otherwise, a predetermined time period is allowed to pass before repeating the process of checking the compliance ofpatient14 with the MACRs associated with the chronic illness(es) ofpatient14 and contactingpatient14 andprovider16. Step192 indicates this delay period.
• When healthcare requests are generated, either as a result of the first path ofFIG. 17 described above, or simply during the ordinary course of employee healthcare consumption,HQM13 receives the healthcare request atstep194. The healthcare request is associated with aparticular patient14 based on the risk stratification process represented bystep182. By determining the risk ranking of the requestingpatient14,HQM13 can perform intervention actions (as described herein) in the order of ranking ofpatients14. In other words, since it is not possible to contact everypatient14 submitting a healthcare request, the ranking ofpatients14 permits HQM13 to focus first onpatients14 having a highest risk ranking, and then (time and resources permitting)patients14 have a smaller likelihood of generating high cost healthcare claims. The method of the present inventionnext accesses database22 to determine whetherprovider16 associated with the healthcare request is currently designated a QSP according to the process described above. Ifpatient14 is requesting to obtain healthcare services from a QSP, then the healthcare request may be processed according to conventional procedures without intervention by representatives ofHQM13 as indicated bystep196. Alternatively, the QSPs resulting from the above-described evaluation process may be ranked relative to one another and categorized into, for example, the “A” and “B” level QSP classifications described above. In such an alternative embodiment, an additional step (not shown) betweenstep196 and step194 of contacting an patient14 requesting healthcare from a “B” level QSP may be provided. At that step, a representative ofHQM13 may attempt to influencepatient14 to obtain such services from a “A” level QSP.
• If, on the other hand, the healthcare request seeks services from a NCQSP, then the ranking of the NCQSP (derived as explained above with reference toFIG. 16) is determined atstep198. Atstep200, a representative ofHQM13contacts patient14 who generated the healthcare request to urgepatient14 to obtain the requested services from a QSP. The representative may explain to patient14 that variousother providers16 within geographic proximity to patient14 (determined in the manner described below) have achieved the QSP designation for high quality, cost efficient healthcare, whileprovider16 selected bypatient14 has not achieved that designation. The representative may further explain the implications of obtaining healthcare services from NCQSPs, and attempt to assistpatient14 in rescheduling the requested healthcare services with a QSP. Additionally, ifpatient14 refuses to switch to a QSP, the representative may attempt to persuadepatient14 to at least switch to a NCQSP that is ranked at a higher level than the currently selected NCQSP.
• As described above, atstep200 ofFIG. 14, the representative ofHQM13 may list forpatient14 the variety of other providers16 (specifically, QSPs) within a specific geographic proximity topatient14. Such a list is generated by accessingdatabase22 using a software interface configured to permit theHQM13 representative to input a desired radius extending from the location ofpatient14, thereby defining an area of geographicproximity surrounding patient14. The software accessesdatabase22, identifies the QSPs located within the selected geographic area, and provides a listing to theHQM13 representative. Using this software and method, the representative may access listings of QSPs within, for example, a five mile, ten mile, and/or fifteen mile radius ofpatient14.
• In theevent patient14 refuses to obtain healthcare services from aprovider16 other than the currently selected NCQSP, the method of the present invention determines (at step202) the level of intervention required to minimize the costs of such services while maintaining high quality healthcare and the specific actions associated with that intervention level. A plurality of actions may be taken by the representative ofTPA12, depending upon the level of intervention required. As described above, the NCQSP listings generated by the present invention may, for example, be divided into thirds (“C,” “D,” and “E” level NCQSPs). “E” level NCQSPs require the greatest level of intervention because the healthcare provided by such NCQSPs, as evaluated by the three QSP tests described herein, most significantly deviates from characteristics associated with desirable healthcare services. “D” level NCQSPs require less intervention. Finally,providers16 designated “C” level NCQSPs require the least intervention. This “stepped-down” approach to intervention permits efficient usage of the resources available toHQM13 in managing the healthcare expenses ofemployer10.
• As indicated above,providers16 at the top third of a NCQSP listing (“E” level NCQSPs) receive the highest level of monitoring and individual contact by representatives ofHQM13. If an “E” level NCQSP is identified atstep198 ofFIG. 17, then step202 obtains a listing of intervention actions associated with “E” level NCQSPs. These actions may include the following:
• • (1) Obtain criteria for any admission associated with the healthcare request, including medical history, tests, and lab work;
  • (2) Delay any admission foremployee14 until all days of admission are approved by an appropriate representative ofHQM13;
  • (3) Complete a telephone evaluation with theNCQSP provider16, conducted by anappropriate HQM13 representative, to evaluate and discuss the need for any admission;
  • (4) Review the need to continue an admission after each day of the admission;
  • (5) Delay any additional days of admission beyond the initial length of stay until such additional days are approved by an appropriate representative ofHQM13;
  • (6) Assign a representative ofHQM13 to provide assistance toprovider16 in determining appropriate services to address the healthcare problem and to report treatments proposed byprovider16 to an appropriate representative ofHQM13; and
  • (7)Contact provider16 directly to discuss any questionable proposed treatments as determined by an appropriate representative ofHQM13.
• If a “D” level NCQSP is identified atstep198 ofFIG. 17, then step202 obtains a listing of intervention actions associated with “D” level intervention. These actions may include the following:
• • (1) Obtain criteria for any admission associated with the healthcare request, including medical history, tests, and lab work;
  • (2) Assign a one-day length of stay and perform daily concurrent review of additional days, requiring approval by an appropriate representative ofHQM13 as needed;
  • (3) Requireprovider16 to send notifications of admissions to an appropriate representative ofHQM13;
  • (4) Complete a telephone consultation withprovider16, conducted by an appropriate representative ofHQM13, if deemed necessary by the representative ofHQM13; and
  • (5) Assign a representative ofHQM13 to provide assistance toprovider16 in determining appropriate services to address the healthcare problem and to report treatments proposed byprovider16 to an appropriate representative ofHQM13.
• Finally, if a “C” level NCQSP is identified atstep198 ofFIG. 17, then step202 obtains a listing of intervention actions associated with a “C” level intervention. These actions may include the following:
• • (1) Obtain criteria for any admission associated with the healthcare request, including medical history, tests, and lab work;
  • (2) Assign a maximum two-day length of stay or less based on conventional length of stay guidelines, and perform daily concurrent review of additional days, requiring approval by an appropriate representative ofHQM13 as needed; and
  • (3) Assign a representative ofHQM13 to provide assistance toprovider16 in determining appropriate services to address the healthcare problem and to report treatments proposed byprovider16 to an appropriate representative ofHQM13.
• All of the various intervention actions listed above are represented bysteps204 and206 ofFIG. 17. After all of the appropriate intervention actions have been completed, the healthcare request is fully processed. Additional healthcare requests may be received atstep194 and simultaneously processed.
• By applying the resources ofHQM13 to intervene with thosepatients14 presenting the greatest risk of generating high healthcare costs andproviders16 most likely to provide the least desirable healthcare, the method of the present invention may result in improvements to the healthcare consumption habits ofpatients14 and to the practice patterns ofproviders16, thereby resulting in an overall improvement of healthcare services consumed bypatients14 and cost efficiency realized byemployer10.
• The foregoing description of the invention is illustrative only, and is not intended to limit the scope of the invention to the precise terms set forth. Although the invention has been described in detail with reference to certain illustrative embodiments, variations and modifications exist within the scope and spirit of the invention as described and defined in the following claims.

Claims (23)

What is claimed is:

1. A method of optimizing healthcare services consumption, including the steps of:

assessing a healthcare situation of a population of patients that reside and consume healthcare services in a geographic zone, the geographic zone consisting of a plurality of geographic regions, each of which includes at least one of a residential address of a patient in the population and a location of a provider who services patients in the population;

using a computing device to transform information generated by the population into data representing a first group of patients from the population likely to have a higher consumption of healthcare services than other patients in the population;

periodically determining whether patients in the first group have obtained healthcare services that satisfy predetermined requirements;

using a computing device to transform information about providers in the geographic zone into identification of a first group of providers in the geographic zone who provide high quality, cost efficient healthcare services relative to other providers in the geographic zone;

prompting patients who have not obtained healthcare services that satisfy the predetermined requirements to obtain additional healthcare services to satisfy the predetermined requirements from providers in the first group of providers; and

communicating with patients to urge the patients to obtain the healthcare services from a provider in the first group of providers.

2. The method ofclaim 1, wherein the assessing step includes the step of comparing costs associated with healthcare services in the geographic zone with costs of similar healthcare services in a geographic area that is larger than the geographic region.

3. The method ofclaim 1, wherein the assessing step includes accessing information describing healthcare data of healthcare consumers in the geographic zone and healthcare consumers outside the geographic zone.

4. The method ofclaim 1, wherein the step of using a computing device to transform healthcare information includes the step of identifying patients suffering from at least one illness.

5. The method ofclaim 1, wherein the step of using a computing device to transform healthcare information includes the step of assigning a healthcare index to each patient based upon factors including age and gender of the patient.

6. The method ofclaim 1, wherein the step of using a computing device to transform information about providers includes the steps of identifying episodes of healthcare for each of the providers in the geographic zone and comparing characteristics of the episodes of healthcare with characteristics of similar episodes of healthcare associated with providers in a geographic area that is larger than the geographic region.

7. The method ofclaim 1, wherein the step of using a computing device to transform information about providers includes the steps of performing an individual calculation for each provider in the geographic zone to determine the provider's cost efficiency index, and assigning a non-certified designation to each provider having cost efficiency index that fails to satisfy a first predetermined condition.

8. The method ofclaim 7, wherein the step of using a computing device to transform information about providers includes the steps of performing an individual analysis for each provider to determine the provider's service rating, and assigning a non-certified designation to each provider having a service rating that fails to satisfy a second predetermined condition.

9. The method ofclaim 8, wherein the step of determining a service rating for each provider includes the step of evaluating the number and types of services ordered by each provider for the treatment of a illness.

10. The method ofclaim 8, wherein the step of using a computing device to transform information about providers includes the steps of evaluating the practice patterns of each provider, and assigning a non-certified designation to each provider having practice patterns that fail to satisfy a third predetermined condition.

11. The method ofclaim 10, wherein the step of using a computing device to transform information about providers includes the steps of assigning a qualified designation to each provider having a cost efficiency index, a service rating, and practice patterns that satisfy the first, second, and third predetermined conditions, respectively.

12. The method ofclaim 1, wherein the prompting patients step includes the step of urging the patients who have not obtained healthcare services that satisfy the predetermined requirements to obtain additional healthcare services from providers in the first group of providers.

13. The method ofclaim 1, wherein the prompting patients step includes the step of attempting to contact the providers of the patients who have not obtained healthcare services that satisfy the predetermined requirements in an effort to persuade the patients to obtain additional services.

14. The method ofclaim 1, further including the steps of ranking the other providers in the geographic zone based on an analysis of the quality and cost efficiency of practice patterns associated with the other providers, dividing the ranking of providers into a second group of other providers having a common characteristic and a third group of other providers having a common characteristic.

15. The method ofclaim 14, wherein the step of ranking the other providers includes the step of assigning a cost efficiency index to each of the other providers.

16. The method ofclaim 14, wherein the step of ranking the other providers includes the step of evaluating a practice pattern characteristic of each of the other providers.

17. The method ofclaim 14, wherein the step of communicating with patients includes the step of urging patients who have obtained services from a third group provider to obtain future services from a second group provider.

18. The method ofclaim 17, wherein the step of communicating with patients includes the step of conducting a first set of intervention actions if the patient uses a second group provider, the first set of intervention actions corresponding to a first degree of involvement of a healthcare quality management representative in the provision of services by the second group provider.

19. The method ofclaim 18, wherein the step of communicating with patients includes the step of conducting a second set of intervention actions if the patient uses a third group provider, the second set of intervention actions corresponding to a second degree of involvement of the healthcare quality management representative in the provision of services by the third group provider, the second degree of involvement being greater than the first degree of involvement.

20. A method of optimizing healthcare services consumption, including the steps of:

assessing a healthcare situation of a population that resides and consumes healthcare services in a geographic region;

using a computing device to transform past healthcare data generated by the population into data representing a first group of patients likely to have a higher consumption of healthcare services than other patients in the population;

periodically determining whether patients in the first group have obtained healthcare services that satisfy predetermined requirements;

using a computing device to transform data representing past practice patterns of providers of healthcare services to the patients into data representing a first group of providers in the geographic region who provide high quality, cost efficient healthcare services relative to other providers in the geographic region;

prompting patients who have not obtained healthcare services that satisfy the predetermined requirements to obtain additional healthcare services to satisfy the predetermined requirements from providers in the first group of providers;

determining whether a patient has obtained healthcare services from a provider not in the first group of providers; and

contacting the patient to urge the patient to obtain healthcare services from a provider in the first group of providers.

22. A method of optimizing healthcare services consumption of a patient population, including the steps of:

transforming using a computing device past data generated by the patients into data representing a first group of patients likely to have a higher consumption of healthcare services than other patients in the population;

transforming using a computing device past practice patterns data of providers who provide services to the patients into data representing a first group of providers who provide high quality, cost efficient healthcare services relative to other providers of the patients;

periodically determining whether patients in the first group suffer from one or more conditions;

determining whether the patients suffering from one or more conditions have obtained healthcare services that satisfy a predetermined set of minimum annual care requirements (MACR) associated with the one or more conditions; and

initiating a communication with a patient who has not obtained healthcare services that satisfy the predetermined set of MACR to instruct the patient to obtain additional healthcare services to satisfy the predetermined set of MACR from a provider in the first group of providers.

23. A system for optimizing healthcare services consumption of a patient population, including:

a first computing device;

a database coupled to the first computing device; and

at least one additional computing device coupled via a network to at least one of the first computing device and the database that provides past data generated by the patients and past practice patterns data of providers who provide services to the patients for storage in the database;

wherein the first computing device includes software having instructions which, when executed by the first computing device, causes the first computing device to

transform the past data generated by the patients into data representing a first group of patients likely to have a higher consumption of healthcare services than other patients in the population,

transform the past practice patterns data into data representing a first group of providers who provide high quality, cost efficient healthcare services relative to other providers of the patients,

periodically determine whether patients in the first group suffer from one or more conditions,

determine whether the patients suffering from one or more conditions have obtained healthcare services that satisfy a predetermined set of minimum annual care requirements (MACRs) associated with the one or more conditions, and

generate a report identifying a patient who has not obtained healthcare services that satisfy the predetermined set of MACRs to prompt communication with the patient to instruct the patient to obtain additional healthcare services to satisfy the predetermined set of MACRs from a provider in the first group of providers.

24. A system for optimizing healthcare services consumption of a population of patients who receive services from providers, including:

a first computing device;

a database coupled to the first computing device;

a second computing device coupled to the first computing device via at least one network; and

a third computing device coupled to the first computing device via the at least one network;

wherein the first computing device receives patient information about the past health of the patients over the at least one network, stores the patient information in the database, and executes software which analyzes the patient information to identify a group of patients having a high likelihood of requiring healthcare services;

wherein the first computing device receives provider information about the practices of the providers, stores the provider information in the database, and executes software which analyzes the provider information to identify a group of preferred providers; and

wherein the first computing device generates at least one report identifying the group of patients and the preferred providers to facilitate attempts to contact a patient in the group to urge the patient to obtain future services from a preferred provider.

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