A Qualitative Analysis of Health Services:

A Non-Parametric Approach in Context with Sabarkantha District

 

Dr. Tusharkumar Shah

Research Scientist, Data Scientist, Development Anthropologist,

GBE Research Foundation, India.

 

 

Abstract:

 

            The health is very important criteria under measure of development phenomenon under every level because its directly related to the human and the society which physical fitness would decides the intensity and capacity of  human and it will be play role under whole development process under region. On the other word, the whole sectors and their development depends on human capacities, skill & efficiency so it would be most require to focus on effective health services are sufficiently providing to last common individual and that leads development phenomenon in every level. The measure of health development is not only depends on number of infrastructure or variable but also it has most require to effectiveness, sufficient level and at time gets services by individual and individual’s satisfaction is most essential under measure of health sector development in the region.

Key Words:   Human, Health Services, Quality, Capacities, Efficiency, Living Level, Development

Introduction:

            The health is indivisible variable from human consistence of life where it’s directly related with individual which examine under unhealthiness would decline under efficiency and productivity as directly negative for growth and development of human & after region too. The Deon Filmer & Pritcheth Lant (1999) has establish relationship between health and income level of individual where higher income individuals are more afford health services than lower holding income, While unfit health and malnutrition would have multiple effects on working time, education, affectivity and individual skills & overall development also.  When individual health is most essential under viability and future of any state or nations, it’s directly responsibility of the respective government for effective & qualitative distribution of health service to the individual. The state has wide duties to establish easy, locally, at timely, cheaply and quality level of services for common individual so health level services has not only affects of quantitative factors but also qualitative factors in the region where evolution of health services are most important measures under qualitative approach due to direct observation of quality & satisfaction level of common individual on different ground level.

The Basic Need Approach (Paul Streeten: 1999) concentrates on full physical, mental and social development as full level development of individuals where living level is centralized under all the aspects. The living level has not limited under only economic level as per above and more than it’s, healthy way of thinking, moral ethics & break psychological constraints makes the better living standards what human really deserves.

            The health services are directly concern with human life with more challengeable day to day as well as it has require extreme technology, R & D, financial strength & wide sphere of services so only once region can’t managing all the level of demands thus many international organization like WHO, UNICEF, UNDP etc are prime considering health on human development in the world. As per WHO (Focal Point Agenda: 21), Human beings are at the centre of concerns for sustainable development, they are entitled to a healthy and productive life in harmony with nature.

Data, Sample & Methodology:

 

The qualitative level research study has main object of inquiries of qualities of services at ground level so in fact it has require direct observation as primary data from selected population and that’s considering here. There would be 676 number of households includes under presents research study where different 13 number of Taluka from all over Sabarkantha district. There has been taken direct households interview under asking different health related quantitative and qualitative questions respected to object of present research study. The different social groups & sub groups are equally random distributed in this sampling distribution as well as it has also more considering to distance level where maintaining proportion of higher distance samples against medium and lower distance samples.

There has different analysis methods are includes under present research study and here non-parametric methods are most applicable under nature of data and object of study. The Simple Sign test which based on Z score value and number of positive and negative sign.

Wilcoxon Signed-Rank test is another non-parametric test based on upon ranking the n1+n2 observations of combined sample. Each observation has give rank as the smallest has rank 1 & 2nd smallest rank 2 and here required Z calculation for both treatments with reason of sample size more than 10 where following formula has applicable:

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*Six major diseases cause 90 percent of death from communicable disease: AIDS, Malaria, Tuberculosis, Pneumonia, Diarrheal Diseases & Measles. (WHO)

**Several Parasitic conditions continue to cause considerable morbidity and disability: Schistosomiasis, Lymphatic Filariasis, Trypanosomizsis & Chagas Diseases where 200 million, 120 million, 55 million & 18 million peoples are affected respectively all over the world. (WHO)

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The Friedman Multiple ANNOVA Test is also one of the alternative analysis tests where it would be applicable if alternative hypothesis would be significance under primary nonparametric test as Kruskal-Wallis Test, sign test and Wilcoxon Signed-Rank test. Here multiple ANNOVA test necessary due to comparison of more than two categories as like under higher satisfied, satisfied, Unsatisfied & Highly Unsatisfied while it has also considering 13 number of factor services over health sector. The object of performing present test is for abstracting contrast among or between different paired categories of satisfaction level under positive and negative consideration.

 

The Factor Services of Health Sector:

• Primary Health Centre
• Community Health Centre
• Referral or District Hospital
• Private Hospital
• Government Support on Sanitation
• Family Welfare Center
• Drainage Facility
• Immunization
• Women Health Supports
• Emergency Care
• Safe Water
• Insurance Company
• ASHA Worker

 

Table: 1

Factors Services Quality Satisfaction Level of Health Sector

(Under Frequency Level)

 

Sr. No	Factor Services	Highly Satisfied	Satisfied	Unsatisfied	Highly Unsatisfied
1	PHC	0	15	20	9
2	CHC	0	39	26	51
3	Referral Hospital	0	72	99	161
4	Private Hospital	8	184	138	80
5	Govt. Support on Sanitation	0	1	4	19
6	Family Welfare Center	11	97	85	52
7	Drainage Facility	0	6	13	8
8	Immunization	14	43	47	16
9	Women Health Supports	40	161	279	196
10	Emergency Care (108)	71	405	195	5
11	Safe Water	4	34	227	411
12	Insurance Company	12	137	103	49
13	ASHA Worker	9	381	156	130

 Source: Author Primary Research Study

 

 

The Table: 1 has representing the outputs of different factors’ services quality level under different satisfaction level in health sector. Here, proportion of highly satisfied household is under different factors have very poor performance where it would be null level under different five factors’ service as well as its also comparative lower than highly unsatisfied in the each factor case except emergency care (108).

The highly unsatisfied has highest 79 percent against highly satisfied & satisfied groups under factor services of fifth as well as it also higher with 60 percent, 48 percent & 44 percent under 11^th, 3^rd & 2^nd factors accordingly.

The satisfied group is highest at 60 percent under emergency care (108) and then after 56 percent, 46 percent, 45 percent & 40 percent highest under 12^th, 11^th, 4^th & 6^th factors accordingly. The unsatisfied group has also highest under drainage facility with 48 percent and also higher with 45 percent, 41 percent, 39 percent & 33 percent under 1^st, 9^th, 8^th & 11^th factors respectively.

The aggregate results of different factors services are most negative because of it has 59 percent score of negative groups as unsatisfied and highly unsatisfied where it has also most higher under most of factors services combine than satisfied and highly satisfied groups thus it has only 41 percent proportion of positive groups which is very poor performance against negative groups.

 

Methodological Test Level Outputs:

 

Sign Test:

The sign test performing on sign of + & – as positive and negative under difference of groups’ treatments as under:

Treatment: 1                                                                Treatment: 2                                                        Diff: (T1 – T2)                                                                        Sign (+ or -)
15		29		-14		–
39		77		-38		–
72		260		-188		–
192		218		-26		–
1		23		-22		–
108		137		-29		–
6		21		-15		–
57		63		-6		–
201		475		-274		–
476		200		276		+
38		638		-600		–
149		152		-3		–
390		286		104		+

 

1. Hypothesis:

            H₀: There is Equal sign of positive & negative treatment from population

            H₁: There is not Equal sign of positive & negative treatment from

       Population where negative sign is excess than positive

 

2. Sign & Z-Score Calculation:

                        Positive sign count = 2

                        Negative sign count = 11

                       Total count = 13

 Z-score Calculation (0.05 significance Level with One Tailed Test)

z = (X – pn) / √npq

z = (11 – 6.5) / √3.25

z = 2.496151

 

3. Result:

The z-value is 2.496151. The p-value is .006277.  So, There is enough evidence      of         reject null hypothesis which claims of equal sign while alternative hypothesis is           significant at p < 0.05 level.

Wilcoxon Signed-Rank Test:

There is calculating the signs, difference between treatment 1 & 2, their rank & also sign rank accordingly.

 

Treatment: 1	15, 39, 72, 192, 1, 108, 6, 57, 201, 476, 38, 149, 390
Treatment: 2	29, 77 ,260, 218, 23, 137, 21, 63, 475, 200, 638, 152, 286
Sign	-1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 1
Absolute Subtraction  treatment 1 & 2	14, 38, 188, 26, 22, 29, 15, 6, 274, 276, 600, 3, 104
Rank	3, 8, 10, 6, 5, 7, 4, 2, 11, 12, 13, 1, 9
Sign Rank	-3 -8 -10 -6 -5 -7 -4 -2 -11 12 -13 -1 9

 

 

1. Hypothesis:

H₀: There is Equal median between sign of positive & negative treatment                       from population

H₁: There is not Equal median between sign of positive & negative                                             treatment from population

2. Z-Score & W-Score Calculation:

Z-value: -1.7122                                          Mean (W): 45.5 Standard Deviation (W): 14.31                   Sample Size (N): 13

W-score:

W-value: 21                             Mean Difference: 57.15 Sum of pos. ranks: 21              Sum of neg. ranks: 70

 

3. Result:

Result 1 – Z-value

The Z-value is -1.7122 & p-value is 0.04363 which is p≤ 0.05 so there is enough evidence to reject null hypothesis of equal median where test significance at level of 0.05 with one tailed.

Result 2 – W-value

The W-value is 21 & critical value of W for N = 13 at p≤ 0.05 is 21. Therefore, the result is significant at p≤ 0.05 as enough evidence to difference between positive & negative groups.

Here, sample size is more than 10 so it has needed to consider Z-Value test rather than W-Value test but both tests are presenting evidence against positive factor services.

 

Friedman Multiple ANNOVA Test:

The Friedman test would perform after significance acceptance of alternative hypothesis for finding contrast level among & between groups where test results as under:

Friedman Test Results

F	15.8571
DF 1	3
DF 2	36
P	<  0.00001

 

The Friedman test is indicating to significance of difference of mean rank in the given groups where Minimum required difference of mean rank: 0.7016 but hear each group have very higher mean rank than minimum and that showing under Table: 2 which indicating to each group has multiple contrasts with highly satisfied. Moreover the highly satisfied has lowest mean which indicating to lowest group among the all while unsatisfied group has highest mean as highest group among all. So obviously, negative group contrast is higher than positive groups where highly satisfied group is most difference with each group.

 

 

Table: 2 Multiple Comparisons

Variable	Mean rank	Different (P<0.05) from variable nr
(1) Highly Satisfied	1.0769	(2) (3) (4)
(2) Satisfied	3.0000	(1)
(3) Unsatisfied	3.2308	(1)
(4) Highly Unsatisfied	2.6923	(1)

 

Table: 3 Descriptive Statistics

Level	n	Minimum	25th  percentile	Median	75th  percentile	Maximum
Highly Satisfied	13	0	0	8	12.5	71
Satisfied	13	1	29.25	72	166.75	405
Unsatisfied	13	4	24.5	99	165.75	279
Highly Unsatisfied	13	5	14.25	51	137.75	411

           

The Table: 3 has reflecting the position of satisfaction level of factors services of health with help of descriptive statistics which shows to median level is very higher under unsatisfied groups and then after satisfied, highly unsatisfied & very lowest under highly satisfied. The maximum level also highest under highly unsatisfied then after satisfied, unsatisfied groups and lowest under highly satisfied group. Moreover, both percentile ratios are higher under negative groups than positive groups where highly satisfied group is always lowest in both levels.

 

Conclusion:

            The different health factor service are tested under different test which clearly showing to highly satisfied group is very lowest than other with specially highly unsatisfied group as well as it would most significant test under differences of median and mean between satisfied & unsatisfied groups where negative unsatisfied combine group is higher than positive satisfied combine group so most health services through different factors is not quite satisfactory and that would be require to re-evolutes and gives preference to planning towards brings satisfaction to common human in district.

           

  Bibliography:

• Deon Filmer & Pritcheth .H. Lant, “The Impact of Public Spending on Health: Does Money Matter?” Social Science & Medicine: 49(10): 1309-23, 1999.
• P. Streeten, “Basic Needs: Premises and Promises”, World Bank Reprint Series, No-62, Journal of Policy Modeling 1, 136-146, 1979.
• World Health Organization, “Health and Sustainable Development: Key Health Trends”, Agenda-21: United Nation Programme for Action, Earth Summit, 2002.
• Donald R. Cooper & Pamela S. Schindler, “Business Research Methods”, 8^th Edition, Tata McGraw-Hill Publishing Company Ltd, New Delhi, 2003.
• Richard I. Levin & David S. Rubin, “Statistics for Management” 7^th Edition, Person Education Asia, Singapore, 2002.