Orchestrating the HIT-GIS

Three of my colleagues have tried to develop GIS like tools to document results, and present them to other authorities.

The first individual made full use of an ArcGIS, trying to get a big business to accept the value of the maps he was producing detailing the communications that went on via typical Verizon networks.  The reason to do this was primarily market related, pertaining the consumer population and how it performs at the regional level.

The second individual used Qlik to produce a visual that was certainly impressive to present, and had some value to it in that if one modified the resolution of the map (zoomed in or out), the data clustering analyses that was undertook adjusted to different areas.  This technician’s idea was that such a map could be used as an automated part of a regular business intelligence review, even to predict health related features of a population based upon regional comparisons.

The third individual had not produced a GIS, just the data for a GIS, and was concerned mostly for live presentation of medical information to whomever needed to use the data.  The idea was that on a regular basis, a physician could obtain access to this live or fairly up to date information and run a query to see how his office was performing relative to the others.  Or, if a patient recently came in with a rare disease, the physician should be able to access of the nearby physicians’ activities records to see if any other cases have presented.

Each of these people had a very different take on how GIS can be used by a healthcare industry.  Chances are, if you come into an an industry already trained in GIS, with a background in GIS applications, your impression of the role and purpose for a GIS will be very different than the impressions these three IT-experienced workers have about its use.  If you are a manager, or chief officer in charge of making serious corporate level decisions about how to advance your company, you may come up with yet another interpretation of the role of GIS in the workplace.

The fact is, GIS can be used for and with all systems that are already present within a given industry.  GIS can be used to manage business level or BI related decision making processes and activities.  GIS can be used to manage your sub-clientele, businesses, colleagues, and gatekeepers, using a GIS as a tool to keep track of your marketing and use of human and physical resources (products).    GIS can be used to manage the business of your industry, or the various smaller units that make up your business, like monitoring the activities related to the various lines of service and allied health services that serve as satellites to your programs.  GIS can be used to manage small businesses and individuals in these businesses, such as doctors and their clinics and their business and service related activities, their cost for the cost of care that they provide their patients.  GIS can also be used to evaluate patients and families, local populations and local events related to health, serving as a thermometer measuring the amount of activity that is going on in the region, serving to provide you with warnings when certain risks become evident, such as not refilling a prescription on time, failing to set up a timely follow up appointment, missing too many of your recommended regular behavioral health visits, not engaging in regular activities design to improve the health of your self or your baby.

To develop a Medical GIS as part of your HIT-GIS system, you have to assign priorities to your various projects.  You also have to evaluate and estimate the amount of work or work hours required for each project, to determine where to assign your priorities, where to put aside the goals of one project manager, in order to better meet the wants and needs of another.

GIS related projects can be assigned priorities in part based upon their predefined need, predefined or estimated time line for that need, and frequency at which this need must be met.  A monthly report requires more monitoring and active engagement than an annual summary report.  A research project designed to tackle a recent issue within the system may require monthly reporting and completion by the end of 6 or 9 months, just before the stockholder’s report is produced for example.  A research project designed to tackle a necessary, although not rushed, research proposal, may take fourth place to three other priorities in GIS known to be considered higher priority.

To orchestrate an HIT-GIS to be constantly productive and the produce more and more products over time, as per the protocols designed for standard PIP and QIA activities, a number of important descriptions or features about the HIT-GIS program have to be designed.  These written statements will then serve as a guide to developing the policy for an HIT-GIS.

The Policy/Statement has to consist of the following:

  • Overall Goal.
  • Objectives (several components of the goal)
  • Examples of statements that meet H0-H1 requirements for the overall program, to determine how they can be assess for completion of incompletion status.
  • A proposed chronology and order for developing the different components of an HIT-GIS.

The following levels of application for Medical GIS have to be evaluated and considered (and reporting procedures, frequency and/or requirements):

  1. Administrative — focused on financial aspects, policy and guidelines development, gatekeepers profiling, benefits cost analyses, foreign language needs requirements, descriptions of special teams, overall regional and business mapping, develop a business intelligence financial database (grants, donations, contributors, new investors), competitiveness, degrees of innovation with examples, unique HR contributions [Annual, some Quarterly]
  2. Services Facility or Equipment — focused on service units, facilities, equipment maintenance, rates of utilization, rates of upkeep and repair, quality assurance, data quality assurance/completeness, flow of money related to contracted services and product or utilization [Annual, Quarterly, Monthly]
  3. Clinical — focused on facility/provider metrics, including the basic measurements, like patients per doctor, patients per specialist, numbers of specialties and specialists, rates of service or performance, numbers of measurable treatment protocols (prescriptions written, EKGs given per year, patient no-shows, complaints, etc.)  [Quarterly, Ad Hoc]
  4. Population/Epidemiological — focused on population and subpopulation health scores and data.  Applies to surveillance and intervention studies.  Applied to investigatory population health programs development. May engage in regional health reporting. May overlap with Special Studies, Administrative, Clinical, and Patient group related activities. Not meant to overlap with public health requirements already in place (violence, infectious diseases); may serve to further research, present and/or map these findings. [Annual review; project reviews or completions; recurring monthly or quarterly reports; large scale reporting for special study topics; automated reporting as much as possible, in HEDIS style for defining administrative and clinical metrics to assess.]
  5. Patient — quality of care to patient; patient survey and survey cards, complaints line, utilization of on-line services and phone services (Hotlines), patient health rates and QOC rates regarding aspects for certain health needs. [Quarterly, Ad Hoc, rolled up to Annual Report]
  6. Special Studies –– listing of all studies (institutional, to private/provider office level), descriptions of most agile or recently completed studies, details on PR and publications policies and products related to studies, normal audiences targeted with studies, special audiences and patient populations or needs targeted with studies; targeted populations, number of people impacted by each study, number and percent of potential people or communities impacted.  [Irregular to Regular, office to institution, large grant to small grant; institutional, educational, descriptive, internal only.  All must have IRB confirmation, approval and remain compliant.]
  7. System — compliance, follow up to complaints rates, types of patient focus group related reviews provided, policy change or development, committees operating and organized.   [Irregular to Regular, weekly to monthly or quarterly, rolled up annually, with certain concepts primarily annual or just once (focus groups)].

A Policy for the Development of a HIT-GIS System in Managed Care – Dissertation related work

The following notes are made regarding the need to define a policy within the managed care setting, when the goal is to produce a spatial analysis or geographic information systems (GIS) tool for implementing full scare spatial monitoring of health at the institutional level.

What is the GIS to be used for?

What are examples of data analyses and institutional quality of care, quality improvement measures that can be applied to spatial analyses for the purpose of defining significant changes, and monitoring quality of care performance?

Based on experience in the managed care setting, and in a national healthdata warehouse setting where GIS was used extensively for a number of years, my analyses revealed the following discoveries about GIS implementation in managed care based population health monitoring programs, and the value of GIS in monitoring cost, quality of services, epidemiological data, surveillance related health concerns, and changes in population health due to system, institutional, population or epidemiological and environmental changes in a region’s areal health patterns.

Policy implementation

Initial Steps:

  1. Design an institutional GIS-HIT Policy; establish a committee devoted to this topic
  2. Define metrics levels, internally and institutionally, and described briefly their potential uses
  3. Define stages and order of development of these different reporting processes and tools
  4. Define stages and levels of reporting the outcomes of any analyses performed using these processes
  5. Have a Report plan and format designed and developed
  6. Establish reporting rights for this data, including methods for:
  • coverage of authorship and inventorship for the processes implemented,
  • IRB related requirements for approvals of release of this information,
  • compliance related details regarding reporting processes,
  • rules for differentiating internal versus external, multiinstitutional versus single institutional reporting and sharing of data and results,
  • administrative versus non-administrative sharing practices for research processes and results,
  • reporting processes normally approved without need for IRB approval using the given data analysis processes,
  • methods for release of information from these projects, methods for warehousing or storage of this data for long term use and reporting purposes,
  • methods for designing the “Atlas” presentation processes for summarizing results,
  • processes related to release of data or findings to outside sources, ranging from other research groups and institutions, to news reporters and press release individuals, to standard refereed medical journal publishers and repositories.

Process for implementing the HIT-GIS tool and program in managed care

  1. Development of a software plan for implement HIT-GIS in a stepwise fashion

Processes for engaging in population health research using this system:

  1. Types of processes involved include standard annual reporting, quarterly reporting, monthly reporting, research related reporting, ad hoc research or pre-research related reporting.
  2. All processes have to undergo internal IRB reviews and a similar review by the IRB sponsoring or supporting the original researcher.
  3. All processes need to have an abstract on the research process, and accompanying documents detailed the data requested and the research processes under consideration; a flowchart is preferred, although not required.
  4. A GANTT diagram or other similar chronological tool should be provided to clarify deadline related requirements.
  5. If available, information on known future users and publishers or the research must be identified.
  6. Sponsors and funding resources for this work must be defined.  If a grant is serving as part of this funding or support, a copy of that grant and/or research proposal should be provided.
  7. A researcher’s bibliography of previously published materials related to this project must be included.  This document must contain recent, up to date materials
  8. A basic information packet must be provided with each major submission of work, which includes:
  • the title of this project,
  • a short title if available for this project,
  • the list of its researchers, including contact and address information and details about their position in the research team,
  • a brief biography of those most involved in this program
  • an abstract on the topic background and history, and the related research processes and methodologies
  • a budget or estimated budgets/cost sheet for the work
  • conflict of interest statement


[34 types, about 1000-2000 metrics, depending upon reports/subgroupings]

The following classes of metrics are defined.  All have been developed and produced in the current managed care system and regional health care system that I am responsible for.  An estimate of the numbers of metrics that are required appears in brackets.

  1. QA – missing data [unk, total ICD? Region, facility?]
  2. Standard metrics – population data on ICDs, plus demographics/area [2-16]
  3. Standard metrics – IH LOS, OP, LOS [7-10],
  4. Standard ICD QOC metrics – Ch Well Visits; CDM Yrly visits; 2MoFU for MH [10-15]
  5. Standard Rx Compliance Measures – Refill rates [2-3]
  6. Ethnicity measure for overall [2-16]
  7. Basic Foreign Language requirement, documentation metric; external use metric? [8,14]
  8. Specific Ethnic ICD/place measures (2 levels) – AfrAm or Hisp, other, Asian, AI/NA [5 each, incl W]
  9. ACOs, MU metrics [45-60]
  10. Other than ACO/QOC-S/MUs, simple basic QIA/PIP metrics (defined elsewhere) [15-20]
  11. HEDIS Admin metrics focused on facilities [25]
  12. Institutional 300+ Disease reporting tool (set for monthly or bimonthly use) [repeats above, 1 report, 300+ metrics]
  13. Ethnic-focused ICD reporting tool/report [40-100, x 4-5, x 8 or 11]
  14. SES-focused reporting tool, with special topics: poverty groups and areas [ditto]
  15. Age-subgroups tools: suicide, epilepsy SUNDS etc. [5-7]
  16. V-codes: ch/adult abuse, abandonment, refusal of care for religious reason, immunization refusal [socially meaningful, 12-15]
  17. ICD codes: suicide risk, special cultural/region risks, ID risks [age/gender related, 7 x 12 = 94]
  18. E Codes:
  19. 65+ yo ICDs report [dupl. above but with different ages, ca. 20-100]
  20. Congenital Diseases report [20-45]
  21. Genetic Diseases report [1-4, or up to 100+ ICDs]
  22. Pregnancy/Child-bearing report (Chlamydia and non-chlamydia, age) [30]
  23. Comprehensive Chronic Disease Mgmt report (2-4 levels) [n cd, 4 grps, 8 regions, 11 facilities, 4-5 ethn]
  24. Charlson Disease list and scores report (totals, levels 1, 4, 6+) [ditto]
  25. Prediction modeling formula/reports (regionally, institutionally, by boroughs; SES-PH, BCBS and OptumHealth “black box” tools) [2 formulas, x 8, 11]
  26. Newborn/Infant Care (3 or 4 years), risk levels (prediction tool) [25-40 icds, x 8,11]
  27. Young:Old Childcare (0-8, 9-17) (tic, beh h, ep, pulm, drug, smoking, alc ab, drug ab, suicide, fx, disl, tc.) (prediction tool) 25-40 icds, x 2 age groups, compared x 8, 11]
  28. Child Schooling (4-17), (Beh H, Nutr, CD, BMI, Injuries, Fx/Disl, ED use) [1 group, ditto]
  29. Mother:Child relationship (families, unmarr. vs married?; 10-45 yo) [1 group, ditto]
  30. Childhd:Adult [changing coverage] QOC conversion rates (asthma, CD, MH), 10-30, 12-26, 15-25/27) [25-40 icds, 8, 11]
  31. Pre-post 65+/- [changing coverage] QOC relationship (55-64, 65-74) [15-40 icds, 2 groups]
  32. SNGs reports: IDs, Autism, EP, MS, PTSD, Specific Drug Abuse hxs, Bullying, Ch Viol. Ch Sx Ab, Age-Fxs, Bioterrorism [15-25 icd small groups, 8, 11]
  33. Special reports, Risk Areas: Child Abuse indicators combination ICDs and V-codes, Suicide, Adult Abuse, Gender specifics; Infib, Violence indicators 6-12 icd subgroups]
  34. Special reports, cultural: culturally-bound indicators, culturally-linked indicators, cultural QOC comparisons (B vs W, H vs W, A vs W) [3 x 40 = 120, starting]
  35. Standardized Special reports: Diabetes, asthma, MS, epilepsy [3-7]

Confirmations and Discoveries – and back to work


Recently, an important observation came my way when I was rerunning one of my many algorithms in a new data set.

These algorithms are fairly basic–well, at least to me they seem that way–and are done, and can be done in several different analysis settings.  I have used them in SQL and SAS environments often, but I invented and discovered some of the math associations in IDRISI.  Now, exposed to Cognos BI, I am looking at another way to run these valuable epidemiology research tools.

The Tableau environment is not so good a tool for this work that I do.  I am seeing the same limitations with Cognos BI.  They allow basic stuff to be done, but the efforts needed to produce a more complex formula are some times–a successful way to test the programmer’s patience and tolerance for over advertised tools, especially when they do little more than the tools already in use.

As I have mentioned before, the production of a 3D algorithm for converting any data to 3D cartographic imagery requires a little time to plan out the process, find the numbers, make new numbers to basemap with, and then the time, patience and effort needed to make your maps (as raster-like images that is).

Most recently, I reran my formula demonstrating the unique assymmetry that can be found between male and female carriers.  This assymmetry tells us that women live long than men in they carry this mysterious disease.  But more importantly, it tells us that women live well into and through their reproductive years.  This means they have the opportunities to potentially bring the gene that causes this disease into the next generation.

Men don’t have the luxury of surviving well into and through their theoretically sexually active years, 30-45.  They start dying off in their late 20s.  Yet, why are they dying?  After all, they are just carriers of the disease, right?


I have no answer to this question, but continue to contemplate its ontogenic nature.  Why did nature make it possible for women to bring that gene on for generation after generation, yet result in men simply dying off for being a carrier?

There is that evolutionary reason we were taught about this disease.  It remains because a mosquito attempting to take the blood of a carrier of this disease will die off once the red blood cells take on the deadly in that mosquito’s gut.  (This mechanism is similar to how Baccilus thurnbergiensis kills mosquitoes, a natural bacterium used to treat potential west nile carrier areas).

But the main point here is that one would think the bizarre shape the population pyramid of patients with this very unique disease takes on.  For me to duplicate it with thousands more cases in a very complete different source of medical data was astounding to see.  It was the first take I took on once I got my new system operating, in some new places.  When I saw the exact same outcomes of years prior, that told me many of the findings produced earlier on a 100M plus population are reliable.  They can add value to my background and knowledge based for evaluating the population health work.

So, back to the algorithm.  It doesn’t need GIS, and too much time has to be spent on GIS to produce what my algorithm effectively produces, for the nation, reviewing more than 100M patients, for a period of about 5 to 20 minutes.  You cannot do that in GIS–produce a map from just thousands of numbers in a three column table, a skill which my algorithm performs quite gracefully.


The Literature Review Process

I have finally reached the literature review process for my dissertation.

To remind the reader of this dissertation and its purpose, it is focused on the use of GIS in medical care, especially managed care.  As a statistician working in a managed care quality improvement program in Colorado, I evaluated about 40,000 members enrolled in Medicaid per year, 1500 enrolled in Medicare, and 4000 to 6500 employees enrolled in the employee health program.

As a part of this activity, I was required to engage in the annual HEDIS review, which consisted of about 15 to 20 research topics (medical conditions or procedures/practices) that had to be manually looked up in the medical records, and another 20 to 25 quality improvement activities (generally an NCQA trademarked term) or performance improvement projects (the term for MCD/ MCR studies) devoted to special research topics (Chlamydia, Diabetes, Asthma care, etc., and one or two per year of the agency’s choice).

A number of these projects involved an assessment of the quality of care process, to determine if barriers existed for meeting certain healthcare goals.  In theory, if those barriers were eliminated, the performance outcomes will demonstrate statistically significant improvement.  These statistically significant improvements were demonstrated using standard Chi Squared or t-Test processes, and occasional Pearson’s Coefficient evaluations.  GIS processes were never utilized.

My first conclusion about this program by the end of the third month was that a population health approach had to be taken.  I therefore developed a population pyramid producing data pull process for the Dell/Perot System UNIX station available to analysts.  This included evaluations of standard demographics information for a total of 250,000 to 500,000 individuals, depending upon the year, and those with service codes for MCD, MCR, CHP and the numerous Employee Health programs provided by this agency.  I then applied these population age-gender study results to the study populations evaluated for each quality improvement study, and some of the former HEDIS defined (inactive, but still researched) QIA projects implemented years earlier.

In developing the Childhood Immunization program PIP, I added Well Visit data to the evaluation process, to determine which well visits were most linked to completion of immunizations by the age of 2 and 5 (two HEDIS measures, and two required NCQA evaluations, performed for each of the three or four programs (if you include CHP)).

I also developed a way to evaluate which clinics had the best and the worst performance.  From this point on, I was engaged in a spatial analytic process of sort, evaluating urban area clinic performance, for clinics that had demographic features differing from each other.  But the use of GIS to engage in this process was only imaginative.

GIS, then, was still at the ArcView GIS level, and PC data limits were at about 10-20 MB for a very expensive high-performing system; a typical system usually was able to manage a 8-10 MB storage, enough for GIS but still quite limiting.

This dissertation serves to develop a process that can be implemented for a managed care system, based on this experience in the office setting of a typical non-SAS friendly managed care quality improvement office setting.

There are several spatial analysis processes that can be applied to managed care–

  1. a crude mapping process using Excel and Excel extensions
  2. a crude process for mapping using a program that is one step up from Excel, such as Tableau
  3. the standard SAS-GIS (which is not user friendly, with or without SAS Enterprise capability),
  4. a process I developed which was 3D modeling of data in SAS, using just SAS-GRAPH, and not requiring GIS
  5. ArcGIS (ESRI) generated spatial analyses
  6. The CDC/NIH spatial analytic tool(s), which are difficult to produce maps with, but strong in terms of their analytic strengths and speed of processing
  7. Any of several other GIS tools now being promoted on the internet for this use (but not texted by myself)

A number of articles will be reviewed, and recommended for those interested in exploring this possible direction as part of the managed care system.  As they are reviewed, they will be added to the following list:

Cresswell, K., & Sheikh, A. (2013). Organizational issues in the implementation and adoption of health information technology innovations: An interpretative review. International Journal of Medical Informatics, 82, e73-e86. doi:10.1016/j.ijmedinf.2012.10.007  Link: CresswellandSheikh_2012_HITBarriers_Int J Med Inform

Kruse, C. S., Regier, V., Rheinboldt, K. T. (2014). Barriers over time to full implementation of health information exchange in the United States. JMIR Medical Informatics, 2(2), e26. doi:10.2196/medinform.3625 Available at http://medinform.jmir.org/2014/2/e26/   Link: Barriers_medinform_v2i2e26

Mair, F. A., May, C., O’Donnell, A., Finch, T., Sullivan, F., & Murray, F. (2012). Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review. Bulletin of the World Health Organization, 90, 357-364. doi:10.2471/BLT.11.099424  Link:  FactorsthatpromoteofinhibitHIT

Transitional Health, Transitional Care – Part 3


Figure 1.  The changes in healthcare in the United States, China and Cuba over Time  

Note: in the US polysectarian (multiple belief  systems) existed for much of the 19th century, followed by solidification or the fields, with allopathy leading, followed by a production of mixed medical practices (MDs and DOs and DCs), maturing into “integrative medicine” (insurance coverage is included) between the 1960s and the 1980s.  Chinese medicine developed a preliminary mixed traditional chinese medicine (TCM) and western allopathy practice due to Hong Kong’s history of British influence and political-economic control.  This caused the first peak in mixed oriental-western European medicine to be fully developed around 1880. In 1950, Mao Tse Tung revived this hybridization of the two practices by demonstrating the use of acupuncture on cardiac surgical patients treated using an up-to-date, western medicine cardiac surgery unit.  This resulted in the continuation of both of these practices and the emergence of other combined TCM and non-TCM Chinese health practices.  Cuba’s program remained typical for one of a developing country.  Mostly western medicine was practiced, with local indigenous and family/cultural practices engaged in on the side.  When communism arrived, there was little change in the western practice, but  socialist teachings had an impact on the quality and types of care to be offered.  Cuba’s greatest changes, along with those of the U.S., were the technological achievements it incorporated.  Cuba has served as an example for developed countries like the U.S. because it  produced  into a very patient-friendly, sociologically integrated, community/family-care  program, referred to as the polyclinic program. (For much more on this history, see brianaltonenmph.com).

 Part 3 

Results of Study

The following are the results of a review of the number of core physicians found in each of the three countries evaluated (Fried & Gaydos, 2012).



Table 1.  Physician:Patient Ratios (Fried & Gaydos, 2012)



Figure 2.  Size-adjusted pie chart depictions of the three healthcare systems, relative to numbers of patients per evaluated primary care provider


Three Types

These are the types of health care providers that service the majority of patients.  A count of the numbers of these physicians, related to the numbers of patients they are responsible for in theory for the entire country, produced the above results.  The relative size of the pie chart depicts the relationship between number of patients per primary care provider (PCP), including some specialists.  The Patient:Practitioner ratio defined the figure size; the pie itself depicts the distributions by degree and specialty.  (Note: no age-gender adjustments were made for this model)

Important to note are the following:

  1. Even though its population is very large, China, has a mid-range ratio for its  Patients per PCP (22,894 patients per practitioner).
  2. The US has the greatest theoretical number of patients per PCP for these data.
  3. Cuba in turn, with its polyclinic set-up, has the greatest number of practitioners per patient available for care.


To compare the differences in how each of these three systems perform, the following depicts those diseases shared by these countries, which have mortality rates that can be evaluated, expressed at numbers of deaths per 100,000 patients, per year:



Table 2.  Death Rates for Six Chronic and One Preventable Disease Groups (

The next section provides figures summarizing the findings from this review.  The ways in which expenses are defined vary greatly between these three programs.  As noted in an earlier figure, reposted here for convenience (Table 3), Cuban government extensively subsidizes its costs for care and in the study of its utilization by Hadad and Allen (2012).  Four key points can be made from this study.


Table 3.  United States, China and Cuban Healthcare Costs, relative to GNP, GDP, with Sources for Payment Plans and Healthcare Coverage.


Point 1.  Due to its size and complexity, the U.S. system demonstrates more details, in terms of forms of expenditures and how these costs are covered (Figures 3 and 4).  The U.S. system has effectively defined its ranking in the international programs, and has plans established on paper for how to best integrate with a theoretical global healthcare program (Figure 5).


Figure 3. United States – Distribution of Expenses (Janjan & Gooman, 2011).


Figure 4.  United States – Distribution of Payers or Programs (Fried & Gaydos, 2012)


Figure 5.  The United States Healthcare Network (Hammond, Jafe, & Kush, 2009)


Point 2.  China also has a fairly sophisticated governing system (simplified greatly in Figure 6).  Chinese medicine also has a greater reliance upon traditional non-allopathic practices (Figure 7).


Figure 6.  Flowchart of Medical and Health Responsibilities and the Ministry of Health in China (Lai,  Hwang, & Beasley, 2011).


Figure 7.  Modern and Traditional Chinese Medicine, Combined to form a Single Program

Point 3.  Cuban healthcare has effectively integrated the former communist government or socialist tradition into its healthcare system.  The reason for its success is often puzzling to outsiders, but a key word used to define why and how it works is the socialist concept and symbolic term or catch phrase “Solidarity.”


Figure 8.  Cuban Polyclinic Medicine Network (right figure redrawn from Hadad & Allen, 2012, 311)

Point 4.  Bringing this back to the initial observation, the interest in managed care and healthcare program changes by Malaysians.  This issue is covered quite extensively in a slide presentation (see also Figure 9), which is fortunately now available on the web (Hamid, 2010).




Figure 9.  The Malaysian Health Care System (Hamid, 2010)


References (this page only)

Fried, B. J., Gaydos, L. M.  (2012). World Health Systems.  Challenges and Perspectives. 2ed. Chicago: Health Administration press.

Gaydos, C. L.  (2012).  United States of America.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems.  Challenges and Perspectives. 2ed. (pp. 693-716).  Chicago: Health Administration Press.

Hadad, J., and Allen, E. M.  (2012).  Cuba.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems. Challenges and Perspectives. 2ed. (pp. 301-316). Chicago: Health Administration Press.

Hamid, M bt A.  (2010).  Care for Malaysia: Restructuring the Malaysian Health System.  Presented at the 10th Malaysia Health Plan Conference by Dato’ Dr Maimunah bt A Hamid, Deputy Director General of Health (Research and Technical Support) 2nd February 2010.  Slide presentation for conference accessed at http://www.slideshare.net/leehualoon/1-care-for-malaysia.

Hammond, W. E., Jafe, C., Kush, R. D. (2009). Healthcare Standards Development. The Value of Nurturing Collaboration. Journal of AHIMA 80 (7), 44-50.  Accessed at http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_043995.hcsp?dDocName=bok1_043995

Janjan, N., Goodman, J.  (2011).  Conflicts of Interest in Health-care Reform?  The ASCO Post, 2 (11), Accessed at http://ascopost.com/issues/July-15-2011.

Lai, D., Hwang, L, Beasley, R. P.  (2011).  HIV/AIDS testing at ports of entry in China. Journal of Public Health Policy 32, 251–262. doi:10.1057/jphp.2011.9

Wen, H., Hung, P., Ji, X., and Li, S.  (2012). China.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems.  Challenges and Perspectives. 2ed. (pp. 251-268).  Chicago: Health Administration Press.




The following are recommended Readings on Chinese, Cuban and Malaysian Health Care Systems:


Chang, J., Guan, Z., Chi, I., Yang, K. H., & Bai, Z. G. (2014). Evidence-based practice in the health and social services in China: developments, strategies, and challenges. International journal of evidence-based healthcare12(1), 17-24. doi: 10.1097/01.XEB.0000444660.59606.d2

Chu, P., & Pai, P. (2015). A new great wall: commissioning a new hospital in China. Future Hospital Journal2(1), 28-33. doi: 10.7861/futurehosp.15.010

Dong, L., Christensen, T., & Painter, M. (2014). Health Care Reform in China: An Analysis of Development Trends and Lack of Implementation. International Public Management Journal, 17(4), 493-514. DOI:10.1080/10967494.2014.958802

En‐Chang, L., Meng, L., Jia, Z., & Ping, L. (2014). 2014 International Bioethics Forum Between UK and China and the Professional Development of Bioethics in China. Bioethics, 28(3), ii-iv.. DOI: 10.1111/bioe.12087

Li, H., Zhang, T., Chi, H., Chen, Y., Li, Y., & Wang, J. (2014). Mobile health in China: Current status and future development. Asian Journal of Psychiatry, 10, 101-104. doi:10.1016/j.ajp.2014.06.003

Song, P., Ren, Z., Theodoratou, E., Guo, S., & An, L. (2014). An analysis of women’s and children’s health professional requirements in China in 2010 based on workload. BMC health services research, 14(1), 589.. doi:10.1186/s12913-014-0589-y

Toy, M., Salomon, J. A., Jiang, H., Gui, H., Wang, H., Wang, J., … & Xie, Q. (2014). Population health impact and cost‐effectiveness of monitoring inactive chronic hepatitis B and treating eligible patients in Shanghai, China.Hepatology60(1), 46-55. DOI: 10.1002/hep.26934. Hou, J., Michaud, C., Li, Z., Dong, Z., Sun, B., Zhang, J., … & Chen, L. (2014). Transformation of the education of health professionals in China: progress and challenges. The Lancet, 384(9945), 819-827.  doi:10.1016/S0140-6736(14)61307-6

Wong, D. F. K., Zhuang, X. Y., Pan, J. Y., & He, X. S. (2014). A critical review of mental health and mental health‐related policies in China: More actions required. International Journal of Social Welfare23(2), 195-204.. DOI: 10.1111/ijsw.12052



Allen, J. A., Bailey, D., Dubus, N., & Wichinsky, L. (2014). The Interrelationship of the Origins and Present State of Social Work in the United States and Cuba: The Power of a Profession to Bridge Cultures. Journal of Human Behavior in the Social Environment, (ahead-of-print), 1-8. DOI:10.1080/10911359.2014.953432

Burke, N. (2014). Review of Revolutionary Medicine: Health and the Body in Post‐Soviet Cuba. P. Sean Brotherton, Durham: Duke University Press, 2012, 288 pp. Medical Anthropology Quarterly, 28(2), b1-b3. DOI: 10.1111/maq.12096

Castro, M., Melluish, S., & Lorenzo, A. (2014). Cuban internationalism-An alternative form of globalization. International Review of Psychiatry, 26(5), 595-601. doi:10.3109/09540261.2014.920770

Cooper, R. S., Kennelly, J. F., & Ordunez-Garcia, P. (2006). Health in Cuba. International journal of epidemiology, 35(4), 817-824

Dubus, N., & Greene, R. (2015). Can the Council on Social Work Education Educational Policy and Accreditation Standards Be Exported to Cuba?. Journal of Human Behavior in the Social Environment, 25(1).

Herman, C., Zlotnik, J. L., Collins, S.  (nd.)  The National Association of Social Workers Leads Delegations to Cuba.  Washington DC: Social Services in Cuba.  Accessed at http://www.ecocubanetwork.net/wp-content/uploads/NASW%20CUBA%20REPORT.pdf

Huish, R. (2014). Why Does Cuba ‘Care’So Much? Understanding the Epistemology of Solidarity in Global Health Outreach. Public Health Ethics, 7(3), 261-276. doi: 10.1093/phe/phu033

McCulloch, A. (2015). Revolutionary Doctors: How Venezuela and Cuba Are Changing the World’s Conception of Health Care. Capital & Class, 39(1), 172.

Rodríguez, A. R. V. (2014). Implications of biotechnology for Public Health in Cuba. Humanidades Médicas 14 (1), 206-219. Accessed at http://philpapers.org/rec/VARIOB.

The story behind Cuba’s deal to send doctors to Brazil.  http://qz.com/234561/the-story-behind-cubas-deal-to-send-doctors-to-brazil/

VEGA, R. A. (2015). Conceiving Cuba: Reproduction, Women, and the State in the Post‐Soviet Era. Elise Andaya. New Brunswick, NJ: Rutgers University Press, 2014. 169 pp. American Ethnologist, 42(1), 190-191.



Hassali, M. A., Li, V., & See, O. G. (2014). Pharmacy practice in Malaysia. Journal of Pharmacy Practice and Research, 44(3), 125-128. DOI: 10.1002/jppr.1024

Inche Zainal Abidin, S., Sutan, R., & Shamsuddin, K. (2014). Prevalence and Determinants of Appropriate Health Seeking Behaviour among Known Diabetics: Results from a Community-Based Survey. Advances in Epidemiology. doi:10.1155/2014/793286

Lee, Y. K., Low, W. Y., Lee, P. Y., & Ng, C. J. (2014). Factors influencing decision‐making role preferences: A qualitative study of Malaysian patients with type 2 diabetes during insulin initiation. International Journal of Nursing Practice. DOI: 10.1111/ijn.12355. http://onlinelibrary.wiley.com/doi/10.1111/ijn.12355/abstract?deniedAccessCustomisedMessage=&userIsAuthenticated=false

Leeves, G., & Soyiri, I. (2015). Does More Education Always Lead to Better Health? Evidence from Rural Malaysia. BioMed Research International. doi:10.1155/2015/539212

Michael, J. M. (2015). The Origins of the Asia-Pacific Academic Consortium for Public Health and the Philosophy Behind Its Establishment. Asia-Pacific Journal of Public Health, 27(1), 7-10. doi:10.1177/1010539514562526

Sooryanarayana, R., Choo, W. Y., Hairi, N. N., Chinna, K., & Bulgiba, A. (2015). Insight Into Elder Abuse Among Urban Poor of Kuala Lumpur, Malaysia—A Middle‐Income Developing Country. Journal of the American Geriatrics Society, 63(1), 180-182. DOI: 10.1111/jgs.13217



Transitional Health, Transitional Care – Part 2



Table 1.  The Costs for Health Care per Capita, as percent of Gross Domestic Product (GDP), along with Purchasing Power Parity per Capita (PPP) 

Source:  World Health Organization (WHO). (2013). WHO Department of Health Statistics and Informatics (May 15, 2013). “World Health Statistics 2013”. Geneva: WHO.   Data accessible via the following website: http://www.who.int/gho/publications/world_health_statistics/2013/en/ 


Part 2

Demographics and Country


This is Part 2 of a three part review of several countries and how their healthcare practices and systems compare and contrast with that of the United States.

Abbreviations in use on this page:

  • GDP – Gross Domestic Product
  • GNP – Gross National Product
  • OECD – Organisation for Economic Co-operation and Development
  • PPP – Purchasing Power Parity per Capita.
  • WHO – World Health Organization

Methodology, Initial Findings, and Discussion

A total of 192 countries are reviewed by the World Health Organization for their cost of care, cost of living, and how these two relate.  The top 20 of these countries for cost are identified and then the four under review for this work (Malaysia, China, Cuba and the United States) were reviewed.

The listing of 192 countries from WHO had four countries that lacked per capita dollars data and/or percent total health expenditure of gross domestic product.  The remaining 188 were compared.  For the comparison,  data were resorted in descending order for Percent of GDP, in order to define the countries that spend the highest percent of money per capita for health care.  This review demonstrated that only one country surpassed the United States (spent 17.6% of GDP) due to the high amounts of money spent per individual per year to become or stay healthy and improve the quality of life–Sierra Leone (spent 20.8% of GDP).

The three countries focused on for this work aside from the United States are China (5.0% of GDP/year), Cuba (10.2%), and Malaysia (not calculated), the latter of which does not have comparable coverage in the book called World Health Systems: Challenges and Perspectives. 2ed, edited by Fried and Gaydos (2012).

The results for these additional  countries are as follows, tabulated along with United States Data:



 Table 2.  PP and GDP calculated for Three of the Four Research Countries for this Study.

Source:  World Health Organization (WHO). (2013). WHO Department of Health Statistics and Informatics (May 15, 2013). “World Health Statistics 2013”. Geneva: WHO.   Data acessible via the following website: http://www.who.int/gho/publications/world_health_statistics/2013/en/ .  An additional value for the U.S. was obtained from OECD Health Division (2013). “OECD Health Data 2013 – Frequently Requested Data”. Paris: OECD.


Figure 1:  A scatter plot produced from Table 1 GDP (x) and PPP data (y).  

Note:  A number of outer ranking or outliers are identified.  The four countries that are the focus of this review are highlighted.

These data were evaluated further to produce a prediction modeling equation for this commercial activity.  Two lines with identical slopes were produced.  One that included the low GDP outliers (lower left corner formula, y-intersect = $2650), and another than focused on the U.S.-Cuba-Malaysia trend (upper left formula equation, y-intersect = $944; comparison of the two, demonstrated p = <.05 for similarity, 94% fit with U.S., Cuba, China, and Malaysia data).  The y-intersect value is considered to be the amount needed up front for engaging in any activities involving the health care program.




Figure 2: Scatter plot or all 188 countries, with two lines drawn.  Line 1, equation in lower left, takes into account the outliers in the lwoer right quadrant.  Focus is on drawing comparisons with the US.  A second line was drawn for linear relationships, excluding the lower right outliers, with y-intersect at -$944.




Figure 3:  Areas of focus, Top 20, relative to more conservative model selected focused on US-Cuba-Malaysia/China financial relationships.  The PPPs are given for each of the countries depicted in yellow.



Figure 4.  Combination of the above country data, population statistics, and two prediction model equations derived from these data.  Note: Cuba is on the edge of top dollar per patient based on PPP, and beyond the -$2650 prediction modeling line; China and Malaysia are relatively low, <5.0 and very close to either of the prediction modeling lines.


The above findings are summarized as follows:


Table 3:  A Comparison of Financial Data for Health Care in the Three Primary Countries Reviewed (WHO, 2013; OECD Health Division, 2013).



World Health Organization (WHO). (2013). WHO Department of Health Statistics and Informatics (May 15, 2013). “World Health Statistics 2013”. Geneva: WHO. Data acessible via the following website: http://www.who.int/gho/publications/world_health_statistics/2013/en/ .

OECD Health Division (2013). “OECD Health Data 2013 – Frequently Requested Data”. Paris: OECD.





Transitional Health, Transitional Care – Part 1


 Figure 1.  Statistics for the Personal Blog Site, Developed for the PhD program at Northcentral University.  Source: Altonen, B.  (2014, March 8).  Stats for March 8, 2015.   Retrieved from https://brianaltonenphd.wordpress.com.


Recently I had a few visitors at my Blog who were from Malaysia.

The majority of my visitors over the years have been from the U.S. and England.  Presumably, that is because my work at this site focuses on western medical traditions and the U.S. managed care system, and is written in English.

My other site, http://brianaltonenmph.com, receives more than 80,000 hits per year, 60,000 visitors, or about 5000 visitors per month (many overlapping).

However, since many countries can speak and read English, I do not expect language barriers to be the determining factor for a visitor.  It ends up, the topics I discuss are why people visit the managed care focused site.    Based on my re-review of the page those four visited– https://brianaltonenphd.wordpress.com/2014/01/22/the-truth-sometimes-hurts-about-healthcare-insurance-industries/ — the page focused on the Quality of Health Care in the up and coming future.  “Seeing the Elephant” was the phrase I assigned to this complex issue we have, the need to be able to more precisely evaluate the quality of care being provided, at home or afar.

seeingtheelephant-ins2 (2)

Figure 2.  Cartoon from my posting “The Truth Sometimes Hurts about Healthcare Industries”, published January 22, 2014,  
at https://brianaltonenphd.wordpress.com/2014/01/22/the-truth-sometimes-hurts-about-healthcare-insurance-industries/


The quality of healthcare is now an international health concern.  We should expect other nations or countries to visit a site that provides its viewers with the best insights into healthcare, U.S. culture, and even health in their own country.

There are several impending crises brewing in health care in general, regarding cost and the quality of care, the transition of care from one form of medicine to the next, the acculturation or “assimilation” of foreign healthcare practices as part of the more global western medical system being promoted, by the World Health Organization as well as the United States and allies.

What is the best form of care to adhere to–a totally U.S.-like system devoted to  technology and western health care paradigms?  the older more traditional culture, but updated, mechanically and staff wise, due to its fitness it has for the country it has served?  of is there a hybrid between the two that can be developed?

Malaysia is one of the countries much like the latter.  It has Oriental and Western paradigms, philosophies and religion.

The following are the facts about Global Health in Malaysia, as well as three countries that will be studied.


Table 1.  Age-Gender Statistics for Four Major Countries Evaluated for this Project.  

Source: The World Factbook 2013-14. (2013). Accessible at https://www.cia.gov/library/publications/the-world-factbook/index.html, or http://www.indexmundi.com/



Table 2.  Demographic Data for 3 of the 4 Countries Evaluated, extracted from the Course Textbook (Wen, Hung & Li, 2012, 252; Hadal & Allen, 2012, 303; Gaydos, 2012, 694).  

Source:  Fried & Gaydos, 2012


 Figure 3.  Population Pyramids for Malaysia, China, Cuba and the United States. 

Source: The World Factbook 2013-14. (2013). Accessible at https://www.cia.gov/library/publications/the-world-factbook/index.html, or http://www.indexmundi.com/   Note:  The Malaysia pyramid is considered a typical outcome for a developed country, due to the very high youth population bands.  China and Cuba produced transitional population age-gender curves.  The United States age-gender results represent a developed country, at a higher economic status.




Central Intelligence Agency.  (2013).  The World Factbook 2013-14. Washington, DC: Central Intelligence Agency.  Accessed at  https://www.cia.gov/library/publications/the-world-factbook/index.html.  Accessible as well at http://www.indexmundi.com/

Fried, B., Gaydos, L. M. (Eds.).  (2012).  World Health Systems.  Challenges and Perspectives.  2ed.  Chicago: Health Administration Press.

Gaydos, C. L.  (2012).  United States of America.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems.  Challenges and Perspectives. 2ed. (pp. 693-716).  Chicago: Health Administration Press.

Hadad, J., and Allen, E. M.  (2012).  Cuba.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems. Challenges and Perspectives. 2ed. (pp. 301-316). Chicago: Health Administration Press.

Wen, H., Hung, P., Ji, X., and Li, S.  (2012). China.  In Fried, B., & Gaydos, L.M. (Eds.) World Health Systems.  Challenges and Perspectives. 2ed. (pp. 251-268).  Chicago: Health Administration Press.